Special Report n° 1/2006
EUROPEAN
ECONOMY
EUROPEAN COMMISSION
DIRECTORATE-GENERAL FOR
ECONOMIC AND FINANCIAL AFFAIRS
The impact of ageing on public expenditure: projections for
the EU25 Member States on pensions, health care, longterm care, education and unemployment transfers
(2004-2050)
Report prepared by the
Economic Policy Committee and the European Commission (DG ECFIN)
The impact of ageing on public expenditure:
projections for the EU25 Member States on
pensions, health care, long-term care, education
and unemployment transfers
(2004-2050)
This report, along with the country fiches prepared by national authorities, is available
on the web sites of the Economic Policy Committee and the Directorate General for
Economic and Financial Affairs of the European Commission:
http://europa.eu.int/comm/economy_finance/epc/epc_publications_en.htm
http://europa.eu.int/comm/economy_finance/publications/eespecialreports_en.htm
2
SUMMARY AND MAIN CONCLUSIONS ............................................................ 5
1.
INTRODUCTION ........................................................................................ 20
2.
UNDERLYING ASSUMPTIONS ................................................................. 24
2.1.
Demographic projections.............................................................................................................24
2.1.1.
The AWG population scenario ..................................................................................................24
2.1.2.
Fertility rates well below replacement levels.............................................................................25
2.1.3.
Continuous increases in life expectancy of more than one year per decade ..............................27
2.1.4.
Net inward migration to the EU projected to continue ..............................................................30
2.1.5.
The size and age structure of the population in the baseline scenario .......................................32
2.2.
Labour force projections .............................................................................................................35
2.2.1.
The cohort component methodology .........................................................................................35
2.2.2.
Projection results for labour force participation and labour supply ...........................................36
2.2.3.
Assumptions on unemployment ................................................................................................38
2.2.4.
Employment rate projections.....................................................................................................40
2.2.5.
A closer look at the impact of ageing on labour supply and employment .................................44
2.3.
Labour productivity and potential growth rates .......................................................................46
2.4.
Other macroeconomic assumptions ............................................................................................50
2.5.
Some overall conclusions on economic impact of ageing ..........................................................50
3.
PENSIONS ................................................................................................. 54
3.1.
Introduction ..................................................................................................................................54
3.2.
Pension schemes and their coverage in the projections.............................................................54
3.2.1.
Overview of the pension systems ..............................................................................................54
3.2.2.
Coverage of the pension expenditure projections ......................................................................62
3.2.3.
The concepts of pensions, contributions and assets...................................................................68
3.3.
Baseline projection results ...........................................................................................................70
3.3.1.
Projected trend in public pension expenditure and a comparison with the 2001 projection......70
3.3.2.
The change in public pension expenditure and its driving factors.............................................77
3.3.3.
Total pension expenditure..........................................................................................................91
3.3.4.
Pensioners and contributors.......................................................................................................96
3.3.5.
Pension contributions and assets of pension funds ..................................................................100
3.4.
4.
Sensitivity analyses .....................................................................................................................104
HEALTH CARE ........................................................................................ 110
4.1.
Introduction ................................................................................................................................110
4.2.
Short overview of the projection methodology ........................................................................113
4.3.
Data used in the projections ......................................................................................................121
4.4.
Results of the budgetary projection exercise............................................................................128
4.4.1.
Pure ageing scenario................................................................................................................128
4.4.2.
Scenario on the health status....................................................................................................129
4.4.3.
Death-related costs ..................................................................................................................129
3
4.4.4.
Income elasticity of demand....................................................................................................130
4.4.5.
Unit costs evolve in line with GDP per worker .......................................................................131
4.4.6.
An AWG reference scenario....................................................................................................132
4.5.
Overall results of the health care projections ..........................................................................133
4.5.1.
A comparison of projection results for all approaches ............................................................133
4.5.2.
Tentative conclusions ..............................................................................................................136
5.
LONG-TERM CARE ................................................................................. 139
5.1.
Introduction ................................................................................................................................139
5.2.
The projection methodology and scenarios..............................................................................141
5.2.1.
Overview of the projection model ...........................................................................................141
5.2.2.
Scenarios carried out in the projection exercise ......................................................................143
5.3.
Data availability and quality .....................................................................................................144
5.3.1.
Age-related expenditure profiles .............................................................................................145
5.3.2.
ADL-dependent population .....................................................................................................149
5.3.3.
Public spending on different types of formal care and unit costs ............................................153
5.4.
Projected size of the dependent population up to 2050 and projected number of persons
receiving different types of care ..............................................................................................................153
5.5.
Projected spending on long-term care ......................................................................................157
5.5.1.
Pure ageing scenario................................................................................................................157
5.5.2.
Unit costs evolve in line with GDP per capita.........................................................................158
5.5.3.
Constant disability scenario.....................................................................................................159
5.5.4.
Increase in formal care provision scenario ..............................................................................159
5.5.5.
AWG reference scenario..........................................................................................................161
5.6.
6.
Conclusion...................................................................................................................................162
EDUCATION............................................................................................. 164
6.1.
Introduction ................................................................................................................................164
6.2.
Data collection and delimitation of the exercise.......................................................................165
6.3.
The number of students in public education............................................................................167
6.3.1.
Demographic developments ....................................................................................................167
6.3.2.
Enrolment ................................................................................................................................169
6.4.
Projections of expenditure on education up to 2050................................................................174
6.5.
Decomposition of the changes in the expenditure shares........................................................176
6.6.
A word of caution .......................................................................................................................180
7.
UNEMPLOYMENT BENEFITS................................................................. 183
7.1.
Description of the projection methodology ..............................................................................183
7.2.
Results of projections for public expenditure on unemployment benefit expenditure.........190
REFERENCES ................................................................................................ 192
LIST OF TABLES ............................................................................................ 201
LIST OF GRAPHS ........................................................................................... 206
4
SUMMARY AND MAIN CONCLUSIONS
The challenge in making comparable cross-country age-related expenditure
projections
In the coming decades, the size and age-structure of Europe’s population will undergo
dramatic changes due to low fertility rates, continuous increases in life expectancy and
the retirement of baby-boom generation. There has been a growing recognition at
national and European level of the profound economic, budgetary and social
consequences of ageing populations. Prompted by the launch of the euro, the Economic
Policy Committee (EPC) established the Working Group on Ageing Populations (AWG)
to examine the economic and budgetary consequences of ageing, which led to the
publication of age-related expenditure projections in 2001 and 2003. On the basis of this
work, an assessment of the long-term sustainability of public finances was integrated into
the surveillance of EU Member States’ budgetary positions, and takes place annually on
the basis of stability and convergence programmes.
In 2003, the ECOFIN Council gave the Economic Policy Committee (EPC) a mandate to
produce a new set of age-related public expenditure projections for all twenty-five
Member States covering pensions, health care, long-term care, education, unemployment
transfers and, where possible, contributions to pensions/social security systems.1 This
report presents these new budgetary projections. It covers the EU10 Member States
which has enriched the exercise, but also increased its complexity and the heterogeneity
of the findings. The projections now provide a better scrutinized and more comparable
set of information for in-depth analysis of risks to the sustainability of public finances.
The unique value-added of these age-related expenditure projections is that they are
produced in a multilateral setting involving national authorities and international
organisations. The projections are made on the basis of a common population projection
and agreed common underlying economic assumptions that have been endorsed by the
EPC.
The projections are generally - and for the reference scenario in particular - made on the
basis of “no policy change”, i.e. only reflecting enacted legislation but not possible future
policy changes (although account is taken of provisions in enacted legislation that enter
into force over time). The pension projections are made on the basis of legislation
enacted by mid 2005. They are also made on the basis of the current behaviour of
economic agents, without assuming any future changes in behaviour over time: for
example, this is reflected in the assumptions on participation rates which are based on the
most recently observed trends by age and gender. While the underlying assumptions have
been made by applying a common methodology uniformly to all Member States, for
several countries adjustments have been made to avoid an overly mechanical approach
that leads to economically unsound outcomes and to take due account of significant
country-specific circumstances.
1
The projections for the EPC were made by the Ageing Working Group of the EPC chaired by Henri
Bogaert and the European Commission’s Directorate General for Economic and Financial Affairs.
5
The pension projections were made using the models of national authorities, and thus
reflect the current institutional features of national pension systems. In contrast, the
projections for health care, long-term care, education and unemployment transfers were
made using common models developed by the European Commission in close cooperation with the EPC and its Working Group on Ageing Populations. While these
projections can point to key drivers of public spending, it needs to be noted that they can
not completely model the specific institutional arrangements and policies which exist at
national level. Caution must be exercised when interpreting the long-run budgetary
projections and the degree of uncertainty increases the further into the future the
projections go. The projections are not forecasts. Instead, they provide an indication on
the potential timing and scale of budgetary challenges that could result from ageing
population based on a “no policy change” scenario. The projection methodologies
employed can not be completely comprehensive, and there are limitations with the data
in several respects.
The age-related expenditure projections presented in this document only portray a partial
picture of the economic and budgetary consequences of ageing populations. For example,
the projected impact of ageing on the labour market and potential GDP growth rates is
based on a partial analysis that does not take account all channels and feedback effects
through which an ageing population could impact on real economic activity. Account
should also be taken of the positive or negative impact of ageing on other public
expenditure and revenue items not covered in this projection exercise. Moreover, and as
recognised in the current framework at EU level for assessing the sustainability of public
finances, account also needs to be taken of the starting underlying budget positions and
outstanding debt levels. In line with the three-pronged strategy, running down public debt
can contribute to the sustainability of public finances.
Improvements compared with the 2001 budgetary projection exercise
The 2005 age-related expenditure projections contain many improvements compared
with the 2001/2003 projection exercise. Many of the shortcomings listed in the EPC
report of 2001 have been addressed, and the following improvements should be
highlighted. With the assistance of Eurostat, a much better understanding of the factors
driving demographic developments has been acquired and particular attention has been
paid to trends in life expectancy. The underlying macroeconomic assumptions were
established in a more coherent and transparent manner; they have been published by the
EPC and European Commission (2005) with quantitative indications of key assumptions
provided wherever possible.2 A more coherent and relevant set of sensitivity tests have
been devised and executed, so that the most important sources of risk to public finances
are examined. Enhanced transparency has been achieved through a structured peer
review process of the results and the national pension models.
The pension projection exercise is broader, now covering nearly all important public
pension schemes, including the old-age provisions for civil servants. To complement
their budgetary projections, countries with statutory private pension schemes have
provided data for these schemes. Some countries have also provided projections for
private occupational pension schemes (with the exception of Denmark and the United
Kingdom).
2
Available under: http://europa.eu.int/comm/economy_finance/publications/european_economy /2005/
eespecialreport0405_en.htm
6
The inclusion of non-demographic drivers in the projection methodology for health care
spending is a significant development. Most progress has been made as regards
modelling the potential impact of changes in the health care status of elderly citizens on
public spending, and on the role played by death-related costs. While data limitations
have been severe, the methodology for projecting public spending on long-term care has
also been significantly extended. Inter alia, it now looks at age-specific disability rates
and enables simulations to be run on future policy changes, such as greater public sector
involvement in the provision/financing of long-term care services and changes in the
balance between the share of formal care provided in institutions and at home.
Large demographic changes are underway
Europe’s population will be slightly smaller, and significantly older, in 2050. Fertility
rates in all countries are projected to remain well below the natural replacement rate. Life
expectancy at birth, having risen by some 8 years since 1960, is projected to rise by a
further 6 years in the next five decades. Inward migration flows will only partially offset
these trends. The total population of the EU25 will register a small fall from 457 to 454
million between 2004 and 2050. Of greater economic significance are the dramatic
changes in the age structure of the population. Starting already from 2010, the workingage population (15 to 64) is projected to fall by 48 million (or 16%) by 2050. In contrast,
the elderly population aged 65+ will rise sharply, by 58 million (or 77%) by 2050. The
old-age dependency ratio, that is the number of people aged 65 years and above relative
to those between 15 and 64, is projected to double, reaching 51% in 2050. Europe will go
from having four people of working age for every elderly citizen currently to a ratio of
two to one by 2050.
Age pyramids for EU25 population in 2004 and 2050
2004
2050
Age
Age
89
85
81
77
73
69
65
61
57
53
49
45
41
37
33
29
25
21
17
13
9
5
1
89
85
81
77
73
69
65
61
57
53
49
45
41
37
33
29
25
21
17
13
9
5
1
5000
4000
3000
2000
Males
1000
0
1000
2000
3000
4000
4000
Females
3000
2000
1000
Males
0
1000
2000
3000
Females
Source: EPC and European Commission (2005)
The change will have major impact on labour market developments
The labour force projection used to make the age-related budgetary projections captures
the impact of an ageing population. The overall employment rate is projected to rise from
63% in 2003 to 67% in 2010 and to reach the 70% Lisbon employment rate target in
2020. The projected increase is mainly due to higher female employment rates, which
will rise from 55% in 2004 to almost 65% by 2025 as older women with low
employment rates retire and are gradually replaced by younger women: the 60% Lisbon
employment rate target for females will be reached in 2010. Even sharper is the projected
increase in the employment rate of older workers, by 19 percentage points from 40% in
2004 to 59% in 2025. This is well in excess of the 50% Lisbon employment target, which
would be reached by 2013. Half of this increase is due to positive effects of already
7
4000
enacted pension reforms, which is a good illustration of the potential benefits of
structural reform.
Projected employment rates and Lisbon targets in the EU25
2050 (p)
2020 (p)
2010 (p)
2004
Older workers
2000
2050 (p)
2010 (p)
2020 (p)
2004
Female
2000
2050 (p)
2020 (p)
2010 (p)
2000
75
70
65
60
55
50
45
40
35
30
2004
Total
Lisbon target
Note:
(p) means projected figures; actual figures are given for 2000 and 2004.
Source: EPC and European Commission (2005)
But demographic forces will dominate and the number of persons employed will
eventually decline
Meeting the Lisbon employment target, even if not on time, will temporarily cushion the
economic effects of ageing. The total number of persons employed is projected to
increase up to 2017, but after 2017, the demographic effects of an ageing population
outweigh this effect. After increasing by some 20 million between 2004 and 2017,
employment will contract by almost 30 million by 2050, i.e. a fall of nearly 10 million
over the entire projection period. Three distinct periods can be identified. Between 2004
and 2011, both demographic and employment developments will be supportive of
growth: this period can be viewed as a window of opportunity for pursuing structural
reforms. Between 2012 and 2017, rising employment rates will offset the decline in the
working-age population: during this period, the working-age population will start to
decline as the baby-boom generation enters retirement. The ageing effect will dominate
as of 2018, and both the size of the working-age population and the number of persons
employed will be on a downward trajectory.
8
Projected working-age population and total employment, EU25
total employment
w orking-age population
employment rate (right scale)
72
320
300
280
p erio d 2 0 0 3 -2 0 11:
rising emp lo yment
b ut slo w g ro wt h in
wo rking -ag e
260
p o p ulat io n
240
220
70
68
p erio d 2 0 12 2 0 17:
rising
emp lo yment
d esp it e t he
d ecline in
wo rking -ag e
f ro m 2 0 18 o nward :
66
emp lo yment and wo rking -ag e p o p ulat io n b o t h d eclining
64
62
200
60
180
58
2003
2008
2013
2018
2023
2028
2033
2038
2043
2048
Source: DG ECFIN
Potential GDP growth is projected to decline
As a result of these employment trends and the agreed assumptions on productivity,
potential GDP growth is projected to decline in the decades to come. For the EU15, the
annual average potential GDP growth rate will fall from 2.2% in the period 2004-2010 to
1.8 % in the period 2011-2030 and to 1.3% between 2031 and 2050. An even steeper
decline is foreseen in the EU10, from 4.3% in the period 2004-10 to 3% in the period
2011-30 and to 0.9% between 2031 and 2050. This is not only due to unfavourable
demographic developments, but also to the underlying assumptions for these countries
which assume productivity growth rates coming closer to those of EU15 countries as
they complete the convergence process.
In addition, the sources of economic growth will alter dramatically. Employment will
make a positive contribution to growth up to 2010, become neutral in the period 20112030, and turn significantly negative thereafter. Over time, labour productivity (due to
the progress of technology) will become the dominant, and in some countries the only,
source of growth. If the projected rise in productivity and in the employment rate will not
materialise in the future, the potential growth may fall even more.
9
Projected (annual average) potential growth rates in the EU15 and EU10 and their
determinants (employment/productivity)
4.0
4.0
4.0
4.0
3.0
3.0
3.0
3.0
2.0
2.0
2.0
2.0
1.0
1.0
1.0
1.0
0.0
0.0
0.0
0.0
-1.0
-1.0
-1.0
2004-10
Labour productivity growth
GDP growth
S i 14
2011-30
2031-50
L a b o u r p ro d u c t iv it y g ro w t h a n d
E m p lo y m e n t g ro w t h
5.0
G D P g ro w th
L ab o u r p ro d u ct ivity g ro w t h an d
Em p lo ym en t g ro w th
EU10
5.0
-1.0
2004-10
Employment growth
GDP per capita growth
S i 15
5.0
2011-30
Labour productivity growth
GDP growth
2031-50
Employment growth
GDP per capita growth
Source: EPC and European Commission (2005)
Overview of the results of the age-related expenditure projections
The table below provides an overview of the projected change in public spending on all
age-related expenditure items between 2004 and 2050. It combines the baseline pension
projection, the 'AWG reference scenario' used for health care and long-term care, the
baseline projected spending on education and the baseline projection for public spending
on unemployment benefits.
Overall, ageing populations is projected to lead to increases in public spending in most
Member States by 2050 on the basis of current policies, although there is a wide degree
of diversity across countries. The following points should be highlighted:
•
for the EU15 and the Euro area as a whole, public spending is projected to increase
by about 4 percentage points between 2004 and 2050;
•
for the EU10, the increase in the overall age-related spending is projected to rise by
only about 1.5 percentage points. This apparently low budgetary impact of ageing is
mainly due to the sharp projected drop in public pension spending in Poland, which
(in common with several other EU10 countries) is partly the result of the switch from
a public pension scheme into a private funded scheme. Excluding Poland, age-related
spending in the other EU10 countries would increase by more than 5 percentage
points of GDP;
• most of the projected increase in public spending will be on pensions, health care and
long-term care. Potential offsetting savings in terms of public spending on education
and unemployment benefits are likely to be limited;
• the budgetary impact of ageing in most Member States starts becoming apparent as of
2010. However, the largest increases in spending are projected to take place between
2020 and 2040;
10
G D P g ro w t h
EU15
5.0
Projected changes in age-related public expenditure between 2004 and 2030/50 (% of GDP)
Pensions
Health care
Level Change from 2004 to:
Level
2004
Long-term care
Change from 2004 to:
Level
Unemployment benefits
Change from 2004 to:
Level
Change from 2004
to:
Education
Level
Change from 2004
to:
Total*
(without
long term care)
Total*
(without
education)
Total* of all
available
items*
Change from 2004
to:
Change from 2004 to:
Change from
2004 to:
2030
2050
2004
2030
2050
2004
2030
2050
2004
2030
2050
2004
2030
2050
2030
2050
2030
2050
2030
2050
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
10.4
9.5
11.4
4.3
3.3
0.9
5.1
3.3
1.7
1.0
1.1
1.0
7.1
2.0
6.4
0.4
7.4
3.5
-1.2
9.7
3.1
0.6
2.0
12.9
5.6
-2.5
6.7
1.8
-1.2
-0.4
-5.9
1.8
7.3
1.4
1.0
1.2
1.7
2.2
1.8
2.0
1.3
1.2
1.3
1.6
0.5
1.4
1.0
1.9
1.1
2.0
1.1
1.0
0.9
1.1
1.8
1.4
1.9
1.6
0.4
0.6
0.4
3.3
1.5
3.1
0.8
5.0
2.9
0.6
4.9
3.3
0.4
1.3
5.3
1.1
-1.9
3.1
1.2
-1.2
1.7
-4.7
0.5
3.4
0.9
0.8
0.9
0.8
1.2
1.2
1.2
0.9
0.8
1.0
1.0
-0.1
1.1
0.7
1.1
0.7
1.4
0.8
0.8
0.7
0.8
1.3
1.0
1.3
1.2
0.9
1.1
1.0
8.6
12.8
4.7
14.2
10.0
7.7
13.4
11.1
10.7
10.6
6.6
6.9
8.5
6.7
10.4
6.7
6.8
7.4
13.9
7.2
11.0
6.2
6.9
6.0
5.1
6.1
7.7
5.3
5.8
5.1
6.1
5.3
6.7
5.6
6.7
7.0
2.9
6.4
5.4
5.5
3.7
5.1
4.2
4.1
4.4
6.4
0.5
0.0
0.2
0.6
1.5
0.9
0.5
0.6
0.1
0.2
0.2
0.3
0.3
0.6
0.7
0.6
0.6
0.9
1.7
3.8
1.0
1.2
1.1
0.3
1.8
1.7
0.8
0.3
0.2
0.4
0.2
0.1
0.2
0.0
0.2
0.5
0.4
0.3
0.2
0.1
0.6
1.2
-0.5
-0.3
-0.4
-0.1
-0.4
-0.3
-0.2
-0.1
-0.0
-0.2
-0.1
-0.1
-0.4
-0.2
-0.0
-0.0
-0.0
-0.0
-0.0
-0.1
-0.1
-0.2
-0.4
-0.2
-0.1
-0.5
-0.3
-0.4
-0.1
-0.4
-0.3
-0.2
-0.1
-0.1
-0.2
-0.1
-0.1
-0.4
-0.2
-0.0
-0.0
-0.0
-0.0
-0.0
-0.1
-0.1
-0.2
-0.4
-0.2
-0.1
5.6
7.8
4.0
3.5
3.7
5.0
4.1
4.3
3.3
4.8
5.1
5.1
6.0
7.3
4.6
6.3
3.8
5.0
4.5
5.0
4.9
4.4
5.0
3.7
5.3
-0.6
-0.4
-0.8
-0.5
-0.7
-0.5
-0.9
-0.8
-0.5
-0.2
-0.9
-0.6
-0.6
-0.7
-0.5
-1.9
-0.9
-1.1
-1.0
-1.6
-1.2
-1.2
-2.0
-1.5
-0.7
-0.7
-0.3
-0.9
-0.4
-0.6
-0.5
-1.0
-0.6
-0.9
-0.2
-1.0
-0.4
-0.7
-0.9
-0.6
-2.2
-0.7
-1.3
-0.7
-1.6
-1.4
-1.2
-1.9
-1.3
-0.4
4.1
3.4
0.6
:
3.3
1.9
3.2
0.9
5.2
3.5
0.5
4.1
3.5
0.3
1.9
4.1
1.6
-2.3
2.8
0.2
-1.7
1.6
-6.1
0.1
3.9
5.3
3.7
1.7
:
8.3
2.9
7.2
1.1
7.6
4.4
-0.7
9.7
3.4
0.5
3.2
11.8
6.8
-2.7
7.0
1.0
-1.6
0.1
-6.8
2.3
8.4
5.1
4.4
1.8
:
4.0
2.4
4.3
1.8
6.0
4.0
1.8
4.7
5.3
2.0
2.7
6.0
2.6
-1.2
3.8
2.0
-0.4
2.9
-4.1
1.8
5.1
7.0
5.1
3.6
:
9.1
3.4
8.8
2.4
9.1
5.2
1.2
10.1
5.9
3.1
4.6
14.1
7.9
-1.4
7.7
3.1
0.1
1.5
-4.8
4.1
10.1
4.5
4.0
1.0
:
3.3
1.9
3.3
1.0
5.4
3.8
0.9
4.1
4.7
1.3
2.2
4.1
1.8
-2.3
2.8
0.3
-1.5
1.8
-6.1
0.3
4.4
6.3
4.8
2.7
:
8.5
2.9
7.8
1.7
8.2
5.0
0.2
9.7
5.2
2.2
4.0
11.8
7.2
-2.7
7.0
1.4
-1.3
0.3
-6.7
2.9
9.7
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
EU9 (EU10-PL)
10.6
10.6
11.5
10.9
8.8
1.3
1.5
1.6
-1.0
1.6
2.2
2.3
2.6
0.3
4.8
6.4
6.4
6.3
4.9
5.5
1.0
1.0
1.0
0.9
0.9
1.6
1.6
1.5
1.3
1.3
0.5
0.4
0.9
0.1
0.7
0.9
0.9
0.9
0.7
0.2
0.3
2.3
1.5
1.3
0.3
1.1
1.2
0.7
0.4
0.3
1.8
0.8
1.0
1.5
1.1
0.4
0.4
0.2
0.1
0.2
0.1
0.3
1.2
0.5
0.3
0.5
0.2
0.3
0.2
0.1
0.2
0.6
0.7
0.5
0.2
0.3
0.9
0.9
1.0
0.4
0.3
-0.3
-0.2
-0.3
-0.2
-0.1
-0.3
-0.2
-0.3
-0.2
-0.1
4.6
4.6
4.4
4.7
4.4
-0.7
-0.6
-0.7
-1.5
-1.1
-0.6
-0.6
-0.6
-1.3
-0.9
1.3
1.6
1.7
-1.8
1.4
2.8
3.0
3.2
0.0
5.1
2.2
2.5
2.5
-0.3
2.6
4.0
4.3
4.4
1.6
6.4
1.6
1.9
1.9
-1.8
1.5
3.4
3.7
3.7
0.2
5.4
EU25
EU15
EU12
EU10
EU9 (EU10-PL)
:
*1) Total expenditure for GR does not include pension expenditure. The Greek authorities have agreed to provide the pension projections in 2006. In the context of the most recent assessment of the
sustainability of public finances based on the Greek stability programme, public spending on pensions was projected to increase by 10.3% of GDP between 2004 and 2050.
2) Total expenditure for: GR, FR, PT, CY, EE, HU does not include long-term care.
3) The projection results for public spending on long-term care for Germany does not reflect current legislation where benefit levels are fixed. A scenario which comes closer to the current setting of
legislation projects that public spending would remain constant as a share of GDP over the projection period.
Note: these figures refer to the baseline projections for social security spending on pensions, education and unemployment transfers. For health care and long-term care, the projections refer to “AWG
reference scenarios”
Age-related spending as a % of GDP in EU Member States, 2004, 2030 and 2050
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
BE
DK
DE
GR
ES
Pensions
FR
Health
IE
IT
Long-term care
LU
NL
Unemploymet benefits
AT
PT
FI
SE
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
0.0
UK
Education
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
CY
CZ
EE
Pensions
HU
Health
LT
LV
Long-term care
MT
Unemploymet benefits
PL
SK
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
0.0
SI
Education
The projection results regarding pensions
For EU15 Member States, public pension spending is projected to increase in all countries,
except Austria, on account of its reforms since 2000. Very small increases in spending on
pensions are projected in Italy and Sweden due to their notional contribution-defined schemes
where pension benefits are based on effective working-life contributions Relatively moderate
increases (between 1.5 and 3.5 percentage points of GDP) are projected in most other EU
countries, with the largest increases projected for Ireland (6.4 p.p.), Spain (7.1 p.p.),
12
Luxembourg (7.4 p.p.) and Portugal (9.7 p.p.). Reforms enacted in several EU15 countries,
since the last age-related expenditure projection exercise of 2001, appear to have curtailed the
projected increase in public spending on pensions significantly in half of all EU15 Member
States3.
The inclusion of the EU10 Member States increases the diversity of the results. Between 2004
and 2030, public pension expenditure is projected to decrease by 1 p.p. of GDP and thereafter
to increase by 1.3 p.p., resulting in an overall increase of 0.3 p.p. of GDP on average between
2004 and 2050. However, the trends are very diverse across countries, ranging from a
decrease of 5.9 p.p. of GDP in Poland and to an increase of 6.7 p.p. in Hungary, 7.3 p.p. in
Slovenia and 12.9 p.p. in Cyprus. The projected decreases in Poland, Estonia and Latvia, as
well as small projected increases in Lithuania and Slovakia, stem partly from pension reforms
enacted during the last 10 years which involve a partial switch of the public old-age pension
scheme into private funded schemes. Thus, the public provision of pensions will decrease
over time while the private part will increase. The challenges faced by Cyprus, Slovenia,
Hungary and the Czech Republic are among the biggest in the EU. While Slovenia and the
Czech Republic have undertaken parametric reforms in their pension system during the 1990s,
the systems remain fully pay-as-you-go public pension schemes.
Decomposing the drivers of public pension spending
A decomposition clearly shows that the rise in the old-age dependency ratio is the dominant
factor pushing up public spending in the coming decades. However, other factors such as
employment rate, eligibility rate and relative benefit level will offset part of the demographic
pressure. In the EU15, these factors are projected to curtail some 70% of the pressure caused
by demographic developments alone, and in the EU10 they would offset almost all the
demographic pressure. The strongest effect will come from the benefit ratio, and in the EU10
countries also from the take-up ratio of pensions. An increase in the employment rate is
projected to help in particular during the next decade, especially in countries with currently
low employment rates.
3
More detailed information about the impacts of enacted reforms are provided in the 'country fiches" published on
the web site of the Economic and Policy Committee:
http://europa.eu.int/comm/economy_finance/epc/epc_sustainability_ageing_en.htm
13
Decomposition of the annual growth of pension spending (as % of GDP)
Decomposition of the pension spending/GDP ratio, EU15
Annual growth
2.50
2.50
2.00
2.00
1.50
1.50
0.91
1.00
0.35
0.50
0.00
-0.17
-0.50
-1.00
A n n u al g ro w th rate, in %
A n n ua l grow th ra te , in %
Decomposition of the pension spending/GDP ratio, EU25
Annual growth
0.95
1.00
0.50
0.31
0.00
-0.09
-0.50
-1.00
-1.50
-1.50
-2.00
-2.00
2005 - 2015
Dependency ratio
Eligibility
2015 - 2030
Benefit ratio
Employment
2030 - 2050
2005 - 2015
Social security pensions, gross as % of GDP
Dependency ratio
2.50
4.00
2.00
3.00
1.50
0.97
1.00
0.50
0.34
0.00
-0.10
-0.50
2015 - 2030
Benefit ratio
Employment
2030 - 2050
Social security pensions, gross as % of GDP
Decomposition of the pension spending/GDP ratio, EU10
Annual growth
-1.00
A n nu al g row th rate, in %
A n n u al g ro w th rate, in %
Decomposition of the pension spending/GDP ratio, EU12
Annual growth
Eligibility
2.00
1.00
0.52
0.85
0.00
-1.00
-1.59
-2.00
-3.00
-1.50
-4.00
-2.00
2005 - 2015
Dependency ratio
Eligibility
2015 - 2030
Benefit ratio
Employment
2005 - 2015
2030 - 2050
Social security pensions, gross as % of GDP
Dependency ratio
Eligibility
2015 - 2030
Benefit ratio
Employment
2030 - 2050
Social security pensions, gross as % of GDP
One of the most striking results is the projected decline in “benefit ratio” of public pensions
relative to wages. It should be noted however, that the benefit ratio, measuring the evolution
of average pensions relative to output per worker, only provides an approximate indication on
the evolution of the generosity of pension systems and is not an equivalent to the usual
replacement rate indicator. The projected fall in the “benefit ratio” is partly due to reforms,
which index pension benefits to prices instead of wages thus reducing the generosity of public
pensions over time. While resulting in budgetary savings, the adequacy of pensions, including
for mixed funded systems, should be kept under review, as it may lead to future pressure for
policy changes. The projected fall in the “benefit ratio” is also the result of the partial switch
from statutory social security pension provision to private funded schemes. While reducing
explicit public finance liabilities and improving the sustainability of public finances, moves
towards more private sector pension provision create new challenges and forms of risks for
policy makers, and in particular, underline the importance of appropriate regulation of private
pension funds and of careful surveillance of their performance for securing adequate
retirement income.
Pension spending is especially sensitive to life expectancy, but less so to changes in the
employment rate
Sensitivity tests show that public spending on pensions appears to be most sensitive to
changes in life expectancy and in some countries to the labour productivity growth rate.
However, the projected change in public spending on pensions are relatively robust regarding
the changes in employment rates and the changes in interest rates affect only funded schemes.
More specifically:
14
• higher life expectancy leads to increased public spending in countries with defined-benefit
schemes, whereas defined-contribution schemes inherently takes into account the length of
retirement. As part of recent pension reforms, some Member States have introduced a link
between life expectancy at retirement and pension benefits: the projection results indicate
that these measures appear to achieve a better sharing of demographic risk.
• a change in the labour productivity assumption only has a significant impact on pension
spending in countries where pension benefits are indexed to prices. In this case, pension
spending as a percentage of GDP will be lower with a higher productivity growth rate
assumption;
• higher employment rates, especially if due to higher employment rates of older workers,
reduce the projected increase in pension spending as a share of GDP. However, the effect
is limited as higher/longer employment results in the accumulation of greater pension
entitlements. Notwithstanding the apparently small impact on public spending, raising the
employment rate is welfare enhancing. It leads to an improved economic performance, and
on the budgetary side it delays somewhat the onset of increased public spending on
pensions. Moreover, higher employment generates increased contributions to pension
schemes, and if it is the result of lower unemployment, additional budgetary savings may
emerge. Finally, longer working lives enable workers to acquire greater pension
entitlements offsetting some of the impact of less generous public pensions.
• interest rates affect the pension spending only in countries where funding is important.
Moreover, it also affects the contribution rate and asset accumulation of funded schemes,
albeit in opposite directions in defined-benefit and defined-contribution schemes. In
defined-benefit schemes, with a higher interest rate, the contribution rate can be lowered to
cover the targeted benefit, whereas in a defined-contribution scheme, the contribution rate
remains unchanged but results in a higher accumulation of assets.
The projection results for health care spending
To project public spending on health care over the long-run is an extremely complex exercise.
There are uncertainties regarding future trends in key drivers of spending, the availability of
comparable data is limited, and the projection methodology which is feasible in a crosscountry exercise is somewhat mechanical and does not reflect the institutional settings for the
provision of health care services in each Member State. A particular challenge has been to
include other non-demographic drivers of spending on both the demand and supply side.
According to the “AWG reference scenario” (a prudent scenario which takes account of the
combined effects of ageing, the health care status of elderly citizens and the income elasticity
of demand), public expenditure on health care is projected to increase by between 1 and 2
percentage points of GDP in most Member States up to 2050. While age itself is not the
causal factor of health care spending (but rather the health condition of a person), the
projections illustrate that the pure effect of an ageing population would put pressure for
increased public spending.
The projections, however, also illustrate that non-demographic factors are relevant drivers of
spending. In particular, the projections show that changes in the health care status of elderly
citizens would have a large effect on health spending. If healthy life expectancy (falling
morbidity rates) evolve broadly in line with change in age-specific life expectancy (a
development which would be equivalent to the so-called dynamic equilibrium hypothesis),
15
then the projected increase in spending on health care due to ageing would be approximately
halved. Caution should be exercised, however, as there is inconclusive evidence that these
‘positive’ trends will occur nor of the scale of their likely impact. Some additional evidence
emerges from a scenario that incorporates death-related costs, i.e. taking account of the fact
that a large share of total spending on health care during a persons lifetime occurs in the final
phase of life.
Compared with the effects of the health care status of elderly citizens, less progress has been
made in incorporating other important supply side drivers of spending into the projection
model. Stylised scenarios indicate that the projected increase in public spending on health
care is very sensitive to the assumption on the income elasticity of demand and on the
evolution of unit costs. Spending on health as a share of GDP could increase at a fast pace if
unit costs (wages, pharmaceutical prices) grow faster than their equivalents in the economy as
a whole, on account of public policies to improve access to health or improve quality (reduce
waiting lists, increase choice), or if rising per capita income levels and the impact of
technology lead to increased demand for health care services. The effective management of
technology is of utmost importance: otherwise the expenditure savings resulting from lower
unit costs could easily be outstripped by the costs of meeting additional demand for new and
better treatments.
The projection results for public spending on long-term care
An ageing population will create a strong upward impact on public spending for long term
care. This is because frailty and disability rises sharply at older ages, especially amongst the
very old (aged 80+) which will be the fastest growing segment of the population in the
decades to come. The projection methodology has been upgraded considerably since the 2001
exercise, and has enabled scenarios to run which examine non-demographic drivers of
spending.
According to the “AWG reference scenario” based on current policy settings, public spending
on long-term care is projected to increase by between 0.1 percentage points and 1.8
percentage points of GDP between 2004 and 2050. This range reflects very different
approaches to the provision/financing of formal care. Countries with very low projected
increases in public spending currently have very low levels of formal care. The projections
show that with an ageing population, a growing gap may occur between the number of elderly
citizens with disability who are in need of care (which will more than double by 2050) and the
actual supply of formal care services. On top of an ageing population, this gap could further
grow due to less informal care being available within households on account of trends in
family size and projected increase in the participation of women in the labour market. In brief,
for countries with less developed formal care systems today, the headline projected increase
in public spending on long-term care may not fully capture the pressure on public finances, as
future policy changes in favour of more formal care provision may be needed.
Public spending is very sensitive to trends in the disability rates of elderly citizens. Compared
with a “pure ageing” scenario, projected change in spending would be between 40% and 60%
lower if the disability status of elderly citizens improves broadly in line with the projected
increase in life expectancy. Policy measures, which can either reduce disability, limit the need
for formal care amongst elderly citizens with disabilities, or which favour formal care at home
rather than in institutions can have a very large impact on public spending.
16
The projection results for public spending on education
The ratio of children and young people to the working-age population is expected to fall over
the coming decades, pointing to fewer students relative to the working population. The pure
consequences of expected demographic changes indicate a potential for a decline in public
expenditure on education in all Member States over the next 50 years, but significant savings
are only projected for some countries. However, this result could be altered substantially, and
public expenditure on education as a share of GDP could even increase if account is taken of
potential rises in enrolment rates due to government efforts to raise skill levels. Overall,
education expenditure cannot be expected to offset the projected increase in spending on
pension and health care expenditures.
The projection results for public spending on unemployment transfers
In order to get a more comprehensive assessment of the total impact of ageing on public
finances, and to guarantee consistency with the macroeconomic scenario, projections on
unemployment benefit spending were also carried out. Unemployment benefit spending in the
EU25 is projected to fall from about 1% of GDP in 2002-2003 to 0.6% in 2025-2050. This
primarily reflects the assumed lower proportions of unemployed people over the projection
period. In terms of percentage points of GDP, the decrease is very modest (given the
relatively low starting levels) and relatively small when compared to projected effects of
ageing on pension and health care spending.
The results overall provide a sound basis for assessing risks to the sustainability of
public finances at EU level…
Overall, the 2005 age-related expenditure projections provide a much more comparable,
transparent and sound basis for the assessment to take place at EU level on the risks to the
sustainability of Member States’ public finances. In the coming months, further analysis is
needed to achieve a fuller understanding of the new projection results, and in particular to get
clearer insights of the key driving factors for each Member States.
Consideration also needs to be given on the possibilities which these new projections offer in
terms of assessing the sustainability of public finances – the annexes provide an overview on
the existing framework. In addressing these issues, the following elements may need to be
taken on board:
•
a major effort has been made to run comparable sensitivity tests on the key drivers of
age-related expenditures. Currently at EU level, a quantitative assessment of fiscal
sustainability is only carried out with reference to a baseline/central projection for agerelated spending (either based on the existing EPC projections or national projections
reported in stability and convergence programmes). The new sensitivity tests offer the
possibility of addressing this shortcoming;
•
for each age-related expenditure item, the reference scenario is to be used for making a
quantitative assessment of the sustainability of public finances. Moreover, national
projections may also be taken into account in the assessment where differences with
the reference scenario and underlying assumptions are clearly described and
explained.
17
…but there is scope for further refinements and analysis
While this new set of common ageing-related expenditure projections represent a substantial
advance compared with earlier exercises, there is scope for further improvements in the
following areas:
•
there is a great deal of uncertainty as regards future trends in life expectancies, and
how these should be handled in a population projection that is used as a basis for
making budgetary projections. The population projection underlying these age-related
expenditure projections embodies considerable differences in projected changes in life
expectancies across countries, which invariably influences the results of the budgetary
projection exercise;
•
migration is also a topic where further analysis is required. Comparable data is very
limited, and there appears to be scope to examine more systematically at EU level the
economic determinants of migration;
•
as regards the macroeconomic assumptions, there appears to be some scope for
improving the approach used regarding productivity, in particular some specific
assumptions and important feedback channels may usefully be further investigated
on the basis of empirical analysis;
•
consideration could be given to projecting an increase in the educational attainment
levels and modelling not only ensuing budgetary effects but also its potential impact
on overall labour productivity;
•
for health care and long-term care, a key challenge is to get to grips with supply side
factors, including the effects of technological changes in health care costs, as well as
to get a better understanding on institutional settings and the incentive effects that they
provide to medical professionals and patients to consume health care services in a
rational manner. An additional element is that the projections only cover public sector
spending, and the interaction with private sector spending on health care would be a
useful extension.
•
regarding the coverage of the exercise, an open question remains to whether additional
age-related expenditure items should be covered, and also on the merits of projecting
the impact of an ageing population on different tax bases and revenues.
•
an area where transparency could be further improved concerns the models used by
Member States to project public spending on pensions. National models are used given
their capacity to capture important institutional characteristics of national pension
systems. This is certainly an important element that is not present in the other
expenditure projections, which can not capture important and specific institutional
features of different national systems. The different approaches to modelling pension
spending have been looked at in a series of peer review, even though the necessarily
high complexity of national models presents some difficulty. Overall, transparency
can be further enhanced by examining in more detail key features of pension models,
not only their general design, but also assumptions regarding the evolution of
thresholds over time, how the transition from work to retirement is modelled and
assumptions on transitions from old to reformed pension schemes.
18
•
Finally, the age-related expenditure projections provide valuable insights on the
budgetary impact of structural reforms, and their use in the context of the Stability and
Growth Pact will be explored further, in time for the assessment of next round of
Stability and Convergence Programmes.
19
1.
INTRODUCTION
The mandate
In the coming decades, the size and age-structure of Europe’s population will undergo
dramatic changes due to low fertility rates, continuous increases in life expectancy and the
retirement of the baby-boom generation. Recently, there has been a growing recognition at
national and European level of the profound economic, budgetary and social consequences of
ageing populations. Prompted by the launch of the euro, the Economic Policy Committee
(EPC) established the Ageing Working Group (AWG) to examine the economic and
budgetary consequences of ageing, which led to the publication of age-related expenditure
projections in 2001 and 2003. 4
In 2003, the ECOFIN Council gave the Economic Policy Committee (EPC) a mandate to
produce a new set of age-related public expenditure projections for all twenty-five Member
States covering pensions, health care, long-term care, education, unemployment transfers and,
where possible, contributions to pensions/social security systems. 5 This report presents these
new budgetary projections. It now covers the EU10 Member States which has enriched the
exercise, but also increased its complexity and the heterogeneity of the findings.
This report presents the results of the age-related expenditure projection exercise. The
projections for the EPC were made by the Ageing Working Group of the EPC Chaired by
Henri Bogaert and the European Commission’s Directorate General for Economic and
Financial Affairs. The AWG members6 are experts from national authorities of all 25 Member
States, the European Commission (represented by the Directorate General for Economic and
Financial Affairs) and the European Central Bank. Eurostat have played a central role by
preparing a population projection.7 Other Commission services are also associated with this
work, especially the Directorate General for Employment, Social Affairs and Equal
Opportunities and the Health and Consumer Protection Directorate General. In addition,
several international organisations have also participated in the AWG’s work on the
budgetary projections, notably the OECD and IMF.8 The EPC has moreover coordinated its
work with other Council formations, especially the Social Protection Committee.9
Overview of the entire age-related expenditure projection exercise
The unique value-added of these age-related expenditure projections is that they are produced
in a multilateral setting involving national authorities and international organisations. The
projections are made on the basis of a common population projection and common underlying
4
Economic Policy Committee (2001) and Economic Policy Committee (2003).
5
Member States can also submit projections for additional expenditure and revenue items, for example family allowances provided they
are based on the agreed underlying assumptions.
6
A list of AWG members can be found in Annex 16.
7
In preparing the population projection, Eurostat has closely involved national statistical institutes via the “Population Projection”
Interest Group on CIRCA, and through meetings of Eurostat’s Working Group on Population Projections.
8
The work of the AWG does not reflect the positions of these international organisations.
9
Its Indicators Sub-Group Chaired by David Stanton.
20
economic assumptions that have been endorsed by the EPC and forwarded to the ECOFIN
Council. The projections are made on the basis of “no policy change”, i.e. only reflecting
enacted legislation but not possible future policy changes (although account would be taken of
provisions in enacted legislation that will enter into force). They are also made on the basis of
the current behaviour of economic agents, i.e. without assuming any future changes in
behaviour over time: for example, this is reflected in the assumptions on participation rates
which is based on the most recently observed participation rates by age and gender (for details
see section 2.2). Every effort has been made to maximise the comparability of the projection
exercise across countries. While the underlying assumptions have been made by applying a
common methodology uniformly to all Member States, for several countries adjustments have
been made to avoid an overly mechanical approach that would lead to economically unsound
outcomes and to take account of significant relevant country-specific circumstances.
Caution must be exercised when interpreting the long-run budgetary projections and the
degree of uncertainty increases the further into the future the projections go. The projections
are not forecasts. There are limitations with the data in several respects and the projection
methodologies employed are not fully comprehensive. Instead, they provide an indication on
the potential timing and scale of budgetary changes that could result from an ageing
population based on a “no policy change” scenario.
It should be emphasised that the budgetary projections presented in this document show only
a partial picture of the economic and budgetary consequences of ageing populations. For
example, the projected impact of ageing on the labour market and on potential GDP growth
rates is based on a partial analysis that does not take into account some channels and feedback
effects through which an ageing population could affect real economic activity. Further the
age-related expenditure projections covered in this exercise may not provide a fully
comprehensive picture of the pressure which demographic change may have on public
finances. For example, the impact of ageing on other public expenditure and revenue items
are not covered in this projection exercise. Moreover, and as recognised in the current
framework at EU level for assessing the sustainability of public finances, account also needs
to be taken of the starting underlying budget positions and outstanding debt levels.
Graph 1-1 below presents an overview of the entire age-related expenditure projection
exercise. The starting point is a common “AWG scenario” population projection for the
period 2004 to 2050. Next, a common set of exogenous macroeconomic assumptions were
agreed, covering the labour force (participation, employment and unemployment rates),
labour productivity and the real interest rate. These combined assumptions enable the
computation of GDP for all Member States up to 2050. On the basis of these assumptions,
separate projections are run for five age-related expenditure items. The projections for
pensions are run by the Member States using their own national model(s). The projections for
health care, long-term care, education and unemployment are run by the European
Commission, on the basis of a common projection model. The results of the set of projections
are aggregated to provide an overall projection of age-related public expenditures.
21
Graph 1-1
Overview of the 2005 projection of age-related expenditure
Assumptions
Projections
Unemployment
benefits
Labour
Productivity
Production function
method
Health
care
Population
2004-2050
Labour
force
AWG scenario
Cohort method
GDP
Long-term
care
Total
agerelated
spending
Education
Unemployment
Convergence to
ECFIN
estimate of NAIRU
Pensions
National models
Real interest
rate
Underlying assumptions endorsed by the ECOFIN Council of November 2005
The population and macroeconomic assumptions to be used for making all the age-related
expenditure projections were endorsed by the EPC and forwarded to the ECOFIN Council in
November 2005. Full details of the underlying assumptions can be found in EPC and
European Commission (2005b). The input data used to calculate the underlying assumptions,
as well as a more detailed description of the projection methodologies can be found in EPC
and European Commission (2005a).
In arriving at the underlying assumptions, the following approach was adopted:
• a review of the economic literature was carried out to identify best practices amongst
international organisations and national authorities in making long-run budgetary
projections;
• on issues where specific expertise was required, a series of workshops were organised at
which external academics and experts were invited;10
10
A list of the conferences can be found in annex 2 of EPC and European Commission (2005 a). The papers and presentations delivered
at the conference on Trends in the health care status and disabilities of elderly citizens held on 21/22 February 2005 can be
downloaded from http://europa.eu.int/comm/economy_finance/events/2005/events_brussels_0205_en.htm . DG ECFIN and the AWG
would like to express their gratitude to Adelina Comas-Herrera and Ilija Batljan who provided advice on projection methodologies to
be used to project health care and long-term care spending during their periods as Visiting Research Fellows in DG ECFIN. The work
of the AWG does not reflect the positions of these individuals, nor of any of the contributors to the workshops/conferences.
22
• the EPC endorsed the underlying assumptions and projection methodologies for the
budgetary projections. Thus, underlying assumptions have been made by applying a
common methodology uniformly to all Member States. To avoid an overly mechanical
approach that can lead to economically unsound outcomes, and to take account of
significant relevant country-specific circumstances, several adjustments were made to the
common approach for several countries. Table 1-1 below provides a summary of these
adjustments which have improved the basis for making the budgetary projections. To
ensure full transparency, the common underlying assumptions and the adjustments are
explained in detail in EPC and European Commission (2005a);
• The AWG invited a number of external experts to provide comments on the robustness of
the underlying assumptions and feasibility of the sensitivity tests. The feedback received
were broadly taken on board;11
Table 1-1 Overview of underlying assumptions and adjustments for certain Member
States
Population AWG scenario
(differences compared with
EUROPOP2004)
Convergence
Data
in lifeadjustment
expectancy
for
across EU15
migration
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PT
PO
SI
SK
FI
SE
UK
Source:
Note:
11
Labour force projections
Data
adjustment
for pension
reforms
Data
adjustment
for
conversion
into
national
account
equivalent
Productivity
Special
convergence
rule on
NAIRU
Data
adjustment
for
conversion
into
national
account
equivalent
TFP
adjustment
to speed the
catch up
with EU15
countries
Real
convergence
of EU10
EPC and European Commission (2005a)
The grey areas indicate the adjustments that have been made.
For a summary of the comments and suggestions of the external experts, see annex 11 of EPC and European
Commission (2005a).
23
Outline of this report
The remainder of this report presents the results of the age-related expenditure projections.
Section 2 recalls the underlying population and macroeconomic assumptions, and draws some
conclusions on the economic impact of ageing populations12. Section 3 portrays the results for
the projections on pension expenditure. Section 4 presents the budgetary projection results for
health care spending and section 5 describes for public spending on long-term care. Lastly,
sections 6 and 7 show the projection results for public spending on education and
unemployment transfers respectively.
This report is complemented with individual country fiches prepared by the authorities of
each Member State. These country fiches are issued under the responsibility of each national
authority. The content of the country fiches is somewhat heterogeneous, but inter alia they
contain a description of the national pension system, a description of the model(s) used to
make the pension projections and an analysis of the main factors driving the results of the
pension projections. Some country fiches contain additional information on the results of the
other age-related expenditure projections as well as information on national strategies to meet
the economic and budgetary impact of ageing.
2.
UNDERLYING ASSUMPTIONS
2.1.
2.1.1.
Demographic projections
The AWG population scenario
The population projection used to make the age-related expenditure projection was prepared
by Eurostat. It is based on, but is not identical to, the EUROPOP2004 projection released by
Eurostat in May 2005,13 and hereafter it is referred to as the “AWG scenario”. In particular:
• the fertility rate assumptions are the same as those in the baseline of EUROPOP2004 for
all 25 Member States;
• for the EU10, the assumptions on life expectancy at birth are the same as those in the
baseline of EUROPOP2004. For the EU15, the assumptions on life expectancy at birth are
based on an AWG scenario produced by Eurostat;
• the migration assumptions are the same as those in the baseline of EUROPOP2004 for all
Member States, except Germany, Italy and Spain, where specific adjustments were made
to the level and/ or age structure of migrants in the AWG scenario.14
12
For a more detailed analysis of the impact of ageing on the real economy and, in particular, on EU labour markets and potential growth
rates, see Carone G., D.Costello, N. Diez Guardia, G. Mourre, B. Przywara, A. Salomäki (2005).
13
‘EU25 population rises until 2025, then falls’, Eurostat press release 448/2005 of 8 April 2005. For simplicity, the baseline variant of
the trend scenario of EUROPOP2004 is referred to as EUROPOP2004 baseline in the text.
14
The migration projections used by the AWG can differ substantially from the migration projections of national authorities. For
example, the Maltese authorities consider that their national projections provide a more reasonable picture of likely future trends and,
therefore, have expressed reservation on the common migration projections.
24
2.1.2.
Fertility rates well below replacement levels
The fertility rate assumptions in the AWG scenario are the same as those used in the baseline
of EUROPOP2004 for all 25 Member States. For the EU15 Member States, fertility is derived
from an analysis of postponement of childbearing and recuperation of fertility rates at a later
age.15 The fertility assumptions for the EU10 Member States have been prepared on the basis
of a study made for Eurostat by the Netherlands Interdisciplinary Demographic Institute
(NIDI). Fertility is postponed as a consequence of modernisation and westernisation; at the
end of the projection period, fertility rates in most EU10 countries are assumed to converge to
an EU average median age at childbearing of 30 years.
Table 2-1 and Graph 2-1 present the fertility assumptions used in the AWG population
scenario. Total fertility rates increase over the projection period in all Member States, except
France, Ireland and Malta, where small declines are projected. In all cases, fertility rates will
remain well below the natural replacement rate of 2.1 needed to stabilise the population size
and age structure. For the EU25,16 fertility rates are projected to rise from 1.48 in 2004 to 1.60
by 2030 and to stay constant around that level until 2050.
15
For an overview of the methodology used, see Eurostat (2004 a).
16
Note that all EU averages are weighted by the population size.
25
Graph 2-1 Past and projected fertility rates for the EU25
2.6
2.4
2.2
2
1.8
1.6
1.4
1.2
1
1970
2004
2020
EU15
2050
EU10
Table 2-1 Baseline assumptions on fertility rates in EU Member states
2004
2010
2020
2030
BE
1.62
1.66
1.69
1.70
DK
1.76
1.78
1.79
1.79
DE
1.35
1.41
1.44
1.45
GR
1.29
1.41
1.49
1.50
ES
1.30
1.36
1.40
1.40
FR
1.89
1.87
1.86
1.85
IE
1.97
1.89
1.81
1.80
IT
1.31
1.38
1.40
1.40
LU
1.65
1.73
1.78
1.79
NL
1.75
1.76
1.75
1.75
AT
1.40
1.42
1.44
1.45
PT
1.45
1.52
1.59
1.60
FI
1.76
1.78
1.79
1.80
SE
1.74
1.84
1.85
1.85
UK
1.72
1.74
1.75
1.75
CY
1.47
1.43
1.49
1.50
CZ
1.15
1.24
1.44
1.50
EE
1.39
1.45
1.54
1.60
HU
1.30
1.33
1.51
1.59
LT
1.29
1.30
1.41
1.55
LV
1.30
1.42
1.53
1.59
MT
1.66
1.49
1.54
1.60
PL
1.21
1.19
1.42
1.58
SK
1.19
1.18
1.33
1.52
SI
1.18
1.27
1.46
1.50
1.48
1.52
1.57
1.59
EU25
1.53
1.57
1.60
1.60
EU15
1.53
1.55
1.56
Euro area 1.49
1.23
1.24
1.44
1.56
EU10
Source: EPC and European Commission (2005a)
2040
1.70
1.80
1.45
1.50
1.40
1.85
1.80
1.40
1.80
1.75
1.45
1.60
1.80
1.85
1.75
1.50
1.50
1.60
1.60
1.60
1.60
1.60
1.60
1.59
1.50
1.60
1.60
1.56
1.58
26
2050
1.70
1.80
1.45
1.50
1.40
1.85
1.80
1.40
1.80
1.75
1.45
1.60
1.80
1.85
1.75
1.50
1.50
1.60
1.60
1.60
1.60
1.60
1.60
1.60
1.50
1.60
1.61
1.56
1.58
change
0.08
0.04
0.10
0.21
0.10
-0.04
-0.17
0.09
0.15
0.00
0.05
0.15
0.04
0.11
0.03
0.03
0.35
0.21
0.30
0.31
0.30
-0.06
0.39
0.41
0.32
0.12
0.07
0.08
0.36
These projected increases are modest as compared with fertility rates observed in other
developed countries such as the US, and point to the prospect of a sustained fall in the size of
the European population. There is substantial divergence in fertility rates between
neighbouring EU countries with similar levels of economic development (e.g. 1.9 children per
woman in FR compared with 1.3 in DE and IT). If sustained over the very long run, these
gaps would lead to very different population prospects. While many countries have public
policies to support families, the majority have not considered explicit strategies targeting
fertility. However, the interaction of a variety of public policies (labour market, education,
and housing) may be inadvertently constrains choices on childbearing, and there is an
emerging interest at EU level as to whether public interventions (e.g. childcare availability,
flexible working-time and leave arrangements) can in practice affect fertility patterns.17
2.1.3.
Continuous increases in life expectancy of more than one year per decade
Life expectancy at birth increased by some 8 years in EU countries between 1960 and 2000,
equivalent to a gain of some 3 months per annum. Eurostat projects these increases to
continue in the decades to come, albeit at a somewhat slower pace.
Table 2-2 and Graph 2-2 present the agreed baseline assumptions on life expectancy at birth
for males and females respectively. Life expectancy at birth for males is projected to increase
by 6.3 years and by 5.1 years for females in the EU25. While this results in some
convergence female life expectancy is nonetheless projected to be 5 years higher than for
males in 2050, at 86.6 years for the EU25 as a whole.
There are significant differences in the life expectancy improvements projected across
Member States. They range from 4.6 years in Sweden to 9.6 in Hungary for males, and from
3.9 years in Spain to 6.6 in Hungary for females. The largest gains in life expectancy are
projected to take place in the EU10, where levels are currently lower than in the EU15 (except
for Cyprus and Malta). Despite this, life expectancy at birth in the EU10 will remain below
the EU15 average according to the projection. This is especially the case for men, with a
projected life expectancy of 78.7 years in 2050 as compared to 82.1 years for the EU15 on
average.
Graph 2-2 Baseline assumptions for life expectancy at birth, EU 15 and EU10
males
Females
0
90
5
85
0
80
5
75
0
70
5
65
0
60
EU15
EU10
1980
2004
2030
EU15
2050
EU10
1980
2004
2030
2050
Source: EPC and European Commission (2005a)
17
In June 2005, the Commission adopted a Green paper Faced with demographic change, a new solidarity between the
generations (COM(2005) 94).
27
These cross-country differences in part reflect the separate approaches used to project life
expectancy at birth between the EU15 and the EU10 countries:
• for the EU10, the assumptions are the same as in the baseline of EUROPOP2004.18 The
method is based on age-specific mortality rates (ASMR) and other mortality indicators
resulting from life tables. Eurostat assumes that the trend of decreasing mortality rates
observed over the period of 1985 to 2002 will continue at the same speed until 2019, and
slow down thereafter. This assumption results in bigger improvements in life expectancy at
birth until 2019 than during the period of 2019 to 2050. Additional assumptions were made
whereby in the medium and long-run, the speed of improvements in mortality reduction
will converge gradually towards the pattern of average improvements in the EU15.
• For the EU15 Member States, the assumptions are based on an AWG scenario produced by
Eurostat on request, for the purpose of making the 2005 budgetary projections. In brief, the
AWG scenario introduces a convergence factor in life expectancy at birth towards the
average outcome of EU15 Member States emerging from the baseline scenario of
EUROPOP200419.
Table 2-2 Baseline assumptions on life expectancy at birth for males and females
s
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
2004
75.5
75.2
76.1
76.4
76.6
76.2
75.5
77.3
75.0
76.2
76.2
74.2
75.3
78.1
76.4
76.3
72.4
65.5
68.5
66.5
64.9
76.2
70.5
69.7
72.6
75.3
76.4
76.3
70.1
2010
76.9
76.4
77.2
77.1
77.6
77.4
76.8
78.3
76.4
77.0
77.4
75.5
76.7
79.0
77.6
77.5
73.7
66.5
70.1
67.4
65.8
77.4
72.0
70.9
73.9
76.5
77.5
77.4
71.6
2020
78.9
78.1
78.9
78.2
79.1
79.3
78.7
79.9
78.4
78.3
79.3
77.4
78.7
80.4
79.4
79.0
75.9
68.9
72.8
69.6
68.0
79.0
74.6
73.1
76.1
78.3
79.1
79.1
74.0
Males
2030
80.3
79.5
80.2
79.3
80.2
80.6
80.2
81.1
79.9
79.4
80.8
79.0
80.2
81.4
80.7
80.2
77.8
71.6
75.2
72.3
70.9
80.1
76.8
75.3
77.9
79.8
80.4
80.3
76.3
2040
81.4
80.6
81.2
80.2
81.0
81.6
81.3
82.1
81.0
80.3
81.9
80.2
81.2
82.1
81.7
81.1
78.8
73.5
77.0
74.3
72.9
81.0
78.2
76.7
78.9
80.8
81.4
81.3
77.7
2050
82.1
81.4
82.0
81.1
81.7
82.3
82.2
82.8
81.8
81.1
82.8
81.2
81.9
82.6
82.4
81.9
79.7
74.9
78.1
75.5
74.3
81.8
79.1
77.7
79.8
81.6
82.1
82.1
78.7
change
6.6
6.2
5.9
4.6
5.1
6.1
6.6
5.5
6.8
4.8
6.6
6.9
6.6
4.6
6.0
5.6
7.4
9.4
9.6
9.0
9.3
5.6
8.7
8.0
7.3
6.3
5.8
5.7
8.6
2004
81.6
79.6
81.7
81.4
83.4
83.4
80.7
83.2
81.4
80.8
82.1
81.0
81.9
82.4
80.9
80.8
78.8
76.9
76.8
77.6
76.2
80.7
78.5
77.8
80.2
81.5
82.2
82.5
78.2
2010
82.9
80.5
82.7
82.1
84.3
84.4
81.8
84.0
82.4
81.4
83.2
82.2
82.8
83.2
82.1
81.6
79.8
77.8
78.0
78.5
76.9
81.7
79.6
78.7
81.2
82.5
83.2
83.4
79.2
2020
84.8
82.1
84.2
83.3
85.6
85.8
83.6
85.3
83.9
82.5
84.7
83.9
84.2
84.4
83.8
82.8
81.3
79.5
79.8
80.1
78.6
82.9
81.3
80.3
82.8
84.1
84.6
84.8
80.9
Females
2030
86.1
83.3
85.4
84.4
86.5
86.8
85.0
86.4
85.1
83.5
85.9
85.2
85.3
85.4
85.1
83.7
82.7
81.2
81.5
81.8
80.4
83.7
82.8
81.8
83.8
85.2
85.7
85.9
82.4
2040
87.0
84.3
86.2
85.2
87.0
87.5
86.0
87.2
86.0
84.4
86.7
86.0
86.0
86.1
86.0
84.5
83.5
82.3
82.6
82.9
81.6
84.4
83.7
82.7
84.6
86.0
86.5
86.6
83.4
2050
87.5
85.2
86.8
85.9
87.3
87.9
86.8
87.8
86.7
85.2
87.2
86.7
86.6
86.6
86.7
85.1
84.1
83.1
83.4
83.7
82.5
85.0
84.4
83.4
85.1
86.6
87.0
87.2
84.1
change
5.9
5.6
5.1
4.5
3.9
4.5
6.2
4.6
5.3
4.3
5.2
5.7
4.8
4.3
5.7
4.3
5.3
6.3
6.6
6.1
6.3
4.3
5.9
5.6
5.0
5.1
4.9
4.7
5.9
18
Eurostat (2004 b)
19
This change was made as the assumptions on life expectancy at birth in EUROPOP2004 are based on an extrapolation
until 2050 of the trends observed during the past 17 years (20 years in some cases), which leads to some divergences
across Member States, including neighbouring countries. The AWG considered that the life expectancy assumptions in
the EUROPOP2004 baseline may not be fully suitable as a starting point for making long-run budgetary projections
whose primary use is to help assess the sustainability of Member States’ public finances. Projected changes in agerelated public expenditures would be heavily determined by the projected (diverging) changes in life expectancy at birth:
this would make it difficult for policy-makers to disentangle the changes in age-related expenditures due to projected
increases in life expectancy from those which are due to the institutional characteristics of national pensions and health
care systems.
28
Source: EPC and European Commission (2005a)
From an economic policy perspective, the following factors regarding life expectancy warrant
special emphasis:
•
much of the projected gains in life expectancy will result from lower mortality rates at
older ages. Life expectancy at 65 for the EU 25 will increase by about 4 years until
2050. This is especially relevant when considering pension policy as it influences the
duration of retirement relative to work;
•
although life expectancy at birth is expected to increase, what is not so clear is
whether future gains in life expectancy will be spent in broadly good health and free of
disability, i.e. whether the overall share of life spent in good health will alter. It is a
highly significant question, not only for the general well-being of older persons, but
also because of its repercussions for health care policy, and is examined in more depth
in section 4;
•
life expectancy projections are subject to uncertainty. Past projections from official
sources have regularly underestimated the gains in life expectancy, and consultations
with external demographic experts suggest that this could also be a risk for current
population projections. Until recently, the so-called ‘demographic risk’ of larger-thanexpected gains in life expectancy has been borne by governments, adding extra costs
to pension systems. Uncertainty has led to a number of technical and policy responses.
To begin with, demographers are trying to improve the understanding of trend
developments and create stochastic population projections attaching probabilities to
future possible outcomes. In addition, some Member States have (through different
means) linked pension benefits to life expectancy at retirement age, thus sharing the
demographic risk between government and pension beneficiary.
29
2.1.4.
Net inward migration to the EU projected to continue
Annual net migration inflows to the EU25 currently amount to 1.3 million people or 0.35% of
the population. The majority of these inflows goes to EU15 countries whereas some EU10
Member States currently experience net outward migration. The assumptions on net migration
in the AWG population scenario are presented on Table 2-3 and
Graph 2-3. These are the same as those used in the baseline of EUROPOP2004 for all
Member States, except for Germany20, Italy and Spain. For the latter two specific adjustments
were made to the level and age structure of migrants (for Spain, changes were only made to
the age structure of migrants). This was done to enable more recent information on migration
flows to be taken on board. The AWG population scenario involves large net flows into the
EU25 over the projection period. For the EU25 as a whole, annual net inflows are projected to
fall from an estimated 1.3 million people in 2004, equivalent to 0.3% of the EU25 population,
to inflows of some 800,000 people by 2015 and thereafter hovering around 850,000 people, or
0.2% of the population.
Graph 2-3 Baseline assumptions on net migration flows, EU 15 and EU10
1600
1400
1200
1000
800
600
400
200
0
1980
2004
2050
-200
EU15 EU10
Source: EPC and European Commission (2005a)
20
The assumptions on net migration in Germany were changed to take into account that the age-structure of migration was
significantly influenced by the reunification and the immigration of German resettlers (Aussiedler) from Eastern Europe.
In addition, the level of net migration was adjusted with a constant net migration of 200,000 "foreigners" p.a. and a
decreasing net migration of German resettlers.
30
Table 2-3 Baseline assumptions on net migration flows for EU Member States
in thousands
2004
2010
2020
2030
2040
BE
24
20
19
19
19
DK
8
7
7
7
7
DE
270
230
215
205
200
GR
43
40
39
35
35
ES
508
112
110
105
104
FR
64
62
60
59
59
IE
16
15
14
13
13
IT
150
150
150
150
150
LU
3
3
3
3
3
NL
21
33
33
32
31
AT
25
24
21
19
20
PT
42
18
16
15
15
FI
6
6
6
6
6
SE
28
24
23
22
22
UK
139
116
103
99
99
CY
6
6
5
5
5
CZ
4
3
10
22
21
EE
1
-2
0
2
2
HU
15
13
14
21
21
LT
-6
-6
-1
5
4
LV
-2
-3
-1
3
3
MT
3
2
2
2
2
PL
-28
-35
-11
36
35
SK
-2
-2
1
5
5
SI
6
6
5
7
7
1343
841
841
895
886
EU25
1347
859
817
788
781
EU15
712
685
660
654
Euro area 1171
-3
-18
24
107
105
EU10
Source: EPC and European Commission (2005a)
2050
19
7
200
35
102
59
12
150
3
31
20
15
6
21
98
5
20
2
20
4
3
3
34
5
7
879
778
651
101
cumulated
897
323
10180
1743
6235
2823
645
7050
132
1480
985
808
288
1069
4939
238
647
19
795
28
30
113
318
109
287
42182
39596
33264
2586
as % of total population
2004
2050
0.2
0.2
0.1
0.1
0.3
0.3
0.4
0.3
1.2
0.2
0.1
0.1
0.4
0.2
0.3
0.3
0.6
0.4
0.1
0.2
0.3
0.2
0.4
0.1
0.1
0.1
0.3
0.2
0.2
0.2
0.0
0.2
0.1
0.2
0.8
0.5
-0.1
0.1
-0.2
0.2
0.1
0.2
0.6
0.5
-0.1
0.1
0.3
0.4
0.0
0.1
0.3
0.2
0.4
0.2
0.4
0.2
0.0
0.1
These net inflows cumulate to close to 40 million people between 2004 and 2050. Migration
is high on the political agenda due to its potential to offset some of the economic effects of
ageing. From an economic policy perspective, the following factors require special emphasis:
• The data on migration flows are sketchy and it is extremely difficult to project migration
flows.21 The static snapshot of net inflows of the AWG population scenario fails to capture
the complexity of the situation, not least because gross flows (both inwards and outwards)
are neglected. Moreover, migration has a dynamic impact on the population of the host
country, and account needs to be taken of factors such as the extent to which migrants
return to their home country, family reunification and whether the fertility and mortality
patterns of migrants’ offspring and subsequent generations converge to that of the host
country. Migration flows are also uncertain due to the influence of a variety of push and
pull factors in both host and home countries (over which the EU have little or no
influence). Natural disasters, war and political instability play a role, but these are too
uncertain to project. Relative income disparities and public policy towards migrants are the
major determining factors of migration over the long-run, and these can be analysed more
21
Eurostat (2004 c).
31
systematically. From an analytical point of view, it is striking to note the very large
diversity in approaches to modelling migration flows across official agencies.22 This
suggests that there may be scope for developing better collaboration at EU level on
analysing migration flows, and in particular to quantify the repercussions of relevant policy
decisions. In addition, for the EU, another important policy determinant is the accession of
new Member States, given the Treaty provisions on the free movement of workers.
• Indeed, several European countries already rely on migrants to fill shortages for certain
skilled and unskilled tasks (e.g. in health care sector). It has been argued that migration
could bolster the financial sustainability of public pay-as-you-go pension schemes. For
these benefits to materialise fully, however, it is necessary for migrants to be employed in
the formal economy (contributing to the tax and social security systems), for pension
schemes to be broadly in actuarial balance (otherwise the contributions of migrants will be
insufficient to cover their future pension entitlements, making the funding of pension
systems potentially not sustainable), and for the skill structure of migrants to match labour
market needs.23 However, in practice however, these conditions are often not met:
immigrants tend to have lower employment rates than EU nationals in many countries, and
their unemployment rates are roughly three times higher than average. Therefore, a key the
challenge is to better integrate immigrants in the society.
2.1.5.
The size and age structure of the population in the baseline scenario
According to the AWG scenario, the population in the EU25 will be both smaller and older in
2050. Table 2-4 provides an overview of these changes. The EU25 population is projected to
rise from 457 million in 2004 to a peak of 470 million in 2025, and thereafter decline to 454
million in 2050. This aggregate picture hides a sharply diverged representation at country
level. Whereas, the total population is projected to increase in some Member States (e.g. BE
+4%, FR +9%, IE +36%, SE +13%, UK +8%), this contrasts with large projected falls in
other countries (DE –6%, IT –7% PL –12%).
22
Howe and Jackson (2005).
23
European Commission Green Paper of January 2005 on managing economic migration (COM (2004) 811 final).
32
Table 2-4 Overview of the projected changes in the size and age structure of the
population, in millions
Total population
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
2004
2050
10.4
5.4
82.5
11.0
42.3
59.9
4.0
57.9
0.5
16.3
8.1
10.5
5.2
9.0
59.7
0.7
10.2
1.4
10.1
3.4
2.3
0.4
38.2
5.4
2.0
456.8
382.7
308.6
74.1
10.8
5.5
77.7
10.7
43.0
65.1
5.5
53.8
0.6
17.6
8.2
10.1
5.2
10.2
64.2
1.0
8.9
1.1
8.9
2.9
1.9
0.5
33.7
4.7
1.9
453.8
388.3
308.4
65.5
%
change
4
2
-6
-3
1
9
36
-7
42
8
1
-4
0
13
8
34
-13
-17
-12
-16
-19
27
-12
-12
-5
-1
1
0
-12
Young
population (0-14)
2004
2050
%
change
Working-age
population (15-64)
2004
2050
%
change
Elderly
population (65+)
2004
2050
%
change
Very old
population (80+)
2004
2050
%
change
1.8
1.0
12.2
1.6
6.2
11.1
0.8
8.2
0.1
3.0
1.3
1.6
0.9
1.6
10.9
0.1
1.6
0.2
1.6
0.6
0.4
0.1
6.6
0.9
0.3
74.8
62.4
48.9
12.4
6.8
3.6
55.5
7.5
29.1
39.0
2.7
38.5
0.3
11.0
5.5
7.1
3.5
5.8
39.2
0.5
7.2
0.9
6.9
2.3
1.6
0.3
26.7
3.8
1.4
306.8
255.1
206.5
51.7
1.8
0.8
14.9
2.0
7.1
9.8
0.4
11.1
0.1
2.3
1.3
1.8
0.8
1.5
9.5
0.1
1.4
0.2
1.6
0.5
0.4
0.1
5.0
0.6
0.3
75.3
65.2
53.3
10.1
0.4
0.2
3.4
0.4
1.8
2.6
0.1
2.8
0.0
0.6
0.3
0.4
0.2
0.5
2.6
0.0
0.3
0.0
0.3
0.1
0.1
0.0
0.9
0.1
0.1
18.2
16.3
13.0
1.9
1.6
0.9
9.5
1.3
5.0
10.4
0.9
6.2
0.1
2.8
1.0
1.3
0.8
1.7
9.4
0.1
1.1
0.2
1.2
0.4
0.3
0.1
4.4
0.6
0.2
61.4
52.7
40.8
8.6
-11
-16
-22
-18
-19
-7
4
-25
26
-9
-24
-21
-13
4
-13
-11
-28
-23
-24
-35
-22
1
-33
-36
-16
-18
-15
-17
-30
6.3
3.3
45.0
5.9
22.9
37.4
3.2
29.3
0.4
10.6
4.7
5.5
3.0
6.0
37.8
0.6
5.0
0.7
5.2
1.7
1.1
0.3
19.4
2.7
1.1
259.1
221.3
174.2
37.8
-8
-8
-19
-21
-21
-4
16
-24
30
-4
-15
-22
-14
4
-4
19
-31
-27
-25
-26
-30
12
-27
-28
-24
-16
-13
-16
-27
3.0
1.4
23.3
3.6
15.0
17.4
1.4
18.2
0.1
4.3
2.5
3.2
1.4
2.5
17.0
0.3
2.8
0.3
2.5
0.8
0.5
0.1
9.9
1.4
0.6
133.3
114.2
93.4
19.1
15
7
105
20
99
94
12
89
1
26
15
18
7
12
93
2
17
1
12
3
1
1
62
10
4
725
613
501
112
1.2
0.5
9.9
1.2
5.3
6.9
0.4
7.2
0.1
1.6
1.0
1.1
0.5
0.9
6.5
0.1
0.8
0.1
0.8
0.3
0.2
0.0
3.0
0.4
0.2
49.9
44.2
36.3
5.7
Source: EPC and European Commission (2005a)
Even more dramatic changes will occur at the age structure of the population. Population
pyramids on Graph 2-4 provide a snapshot contrast of the EU25 population in 2004 and 2050.
In 2004, the large bulges are persons of working age, with 39 being the most numerous age
cohorts. By 2050, an inverted cone shape is evident, reflecting the passage of baby-boomers
into retirement years, increasing life expectancy and the effects of prolonged low fertility
rates.
33
173
140
187
227
199
163
313
158
279
191
204
181
174
95
150
319
164
124
131
171
131
254
226
210
252
174
172
180
193
Graph 2-4 Age pyramids for the EU25 population in 2004 and 2050
2050
2004
Age
Age
89
85
81
77
73
69
65
61
57
53
49
45
41
37
33
29
25
21
17
13
9
5
1
89
85
81
77
73
69
65
61
57
53
49
45
41
37
33
29
25
21
17
13
9
5
1
5000
4000
3000
2000
M ales
1000
0
1000
2000
3000
4000
4000
3000
2000
Female s
1000
M ales
0
1000
2000
3000
4000
Female s
Source: EPC and European Commission (2005a)
As illustrated on Graph 2-5, the share of young persons aged 0-14 in the total population is
projected to decline, and their overall numbers in the EU25 will drop by 19% (-30% in
EU10). From an economic perspective, the most interesting change concerns the working-age
population (15-64). This group will start to fall as of 2010 in the EU25 (sooner in some
countries), and drop by 48 million or 16% by 2050. Here Member State divergences are wide,
with declines of more than 20 percentage points projected in 13 countries (DE, GR, ES, IT,
PT, CZ, EE, HU, LT, LV, PL, SK, SI). In contrast, the elderly population aged 65+ will rise
sharply, by 58 million (or 77%), by 2050. The fastest growing segment of the population will
be the very old (80+) and rise by almost 32 million or 174%.
Graph 2-5 Projected changes in the age structure of the EU25 population
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
2004
2010
2020
0-14
2030
15-64
Source: EPC and European Commission (2005a)
34
65-79
2040
80+
2050
2.2.
2.2.1.
Labour force projections
The cohort component methodology
“No policy change” assumption in baseline scenario
The labour force projection is based on an age-cohort methodology developed by the OECD24
and refined by DG ECFIN25 and the AWG. The methodology takes into account explicitly the
evolution of lifetime profiles of participation. It is based on the calculation of the probability
of labour market entry and labour market exit for each of the latest cohorts available (based
on the average rates between 1998 and 2003). These probabilities are kept constant and, in the
baseline scenario, reflect a working assumption of “no policy change”. In essence:
• the cohort methodology reflects the tendency for women belonging to any given cohort or
generation to have their own specific level of participation, which is usually higher at all
ages than the corresponding level of participation of older cohorts. Thus, the simulation
produces an autonomous increase of female participation – referred to as a “cohort effect”
– as older women are gradually replaced by younger cohorts;
• captures the effects of demographic change on the labour force. Besides the reduction in
the size of the working-age population (aged 15-64), an ageing population also increases
the share of older workers (aged 55-64) in the total labour force, whose participation rate is
significantly lower than that of younger age groups.
Projections on the future size and structure of the labour force are obtained by combing
projections of activity rates (of each single year of age and gender of people in the labour
market) with the baseline working-age population projection described in section 2.1. The
employment projections only refer to the number of persons, and it is assumed that over the
projection period, there will be no changes in the hours worked, the breakdown between
private and public sector, the share of self-employed and employees, or the share of part-time
work.
Some additional assumptions on participation rates
The following additional adjustments were also included in making the labour force
projections:
• a correction mechanism for young cohorts: a floor at the rate observed in 2003 was applied
to the participation rates of young cohorts (aged 15-19) in some countries. This is to avoid
extrapolating over the next 50 years the recently observed drop in the participation rates of
young cohorts as a result of the extended duration of full-time education;
• the potential effects of recently enacted pension reforms that will be phased-in in 17 EU
Member States are considered. These include reforms to increase statutory retirement ages,
to curtail access to early retirement schemes and to remove financial incentives that have
24
Burniaux J., M., R. Duval and F. Jaumotte (2003).
25
A more detailed description of the projection methodology and results can be found in Carone (2005).
35
encouraged workers to leave the labour force26. The effects of these pension reforms have
been modelled using a probabilistic model already used within the European Commission
for the calculation of the “average exit age” from the labour force;
• for a number of Member States, the conversion of labour force projections is based on
Labour Force Surveys that have been converted into national account equivalents.27
2.2.2.
Projection results for labour force participation and labour supply
Projected increases in overall participation rates
Table 2-5 presents the participation rates by age group and gender in the EU25 Member States
in 2003, and Table 2-6 shows the projected change up to 2050 used in the baseline scenario.
Overall participation rates (for the age group 15-64) in the EU25 are projected to increase by
about 6 percentage points over the period 2003-2050 (from 69.4% in 2003 to 74.6% in 2025
and to 75.2% in 2050).
26
Detailed information on pension reforms enacted in the EU Member States (also migration policy) can be found in a
new database on labour market reforms (LABREF) recently launched by the European Commission-Directorate General
for Economic and Financial Affairs together with Labour Market Working Group attached to the EPC. LABREF can be
found at: http://europa.eu.int/comm/economy_finance/indicators/labref_en.htm. A description of the database can be found in
Arpaia A, D. Costello, G. Mourre and F. Pierini (2005), and the economic rationale for tracking changes in labour
market institutions can be found in Arpaia and Mourre (2005).
27
In many countries, employment data from Labour Force Surveys differ significantly from data from National Accounts
due to different statistical methodologies. For some countries, where e.g. pension models are based on National
Accounts, a conversion was implemented to avoid inconsistencies.
36
Table 2-5 Participation rates by gender and age group in 2003 in EU Member States
Total
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
Male
Female
Total
Young
Prime age
Older
Total
Young
Prime age
Older
Total
Young
Prime age
Older
(15-64)
(15-24)
(25-54)
(55-64)
(15-64)
(15-24)
(25-54)
(55-64)
(15-64)
(15-24)
(25-54)
(55-64)
65.0
35.2
82.3
28.9
72.9
38.6
90.9
38.8
56.9
31.6
73.6
19.3
79.3
65.2
87.8
62.8
83.7
67.8
91.7
70.4
74.8
62.4
83.8
55.2
72.6
50.1
86.2
45.2
79.5
52.9
93.3
54.7
65.4
47.1
78.8
35.9
65.3
35.8
80.0
43.5
78.1
39.3
94.4
61.4
52.4
32.0
65.4
27.1
67.5
44.7
79.6
43.6
79.9
49.8
92.5
62.8
55.1
39.3
66.5
25.6
69.3
38.5
86.3
38.3
75.4
42.7
93.4
42.7
63.3
34.2
79.2
34.0
68.8
52.4
79.1
50.1
79.2
56.1
91.0
66.2
58.3
48.6
67.2
33.6
62.9
37.8
77.9
30.5
74.9
41.6
91.6
43.1
50.9
34.0
64.1
18.8
65.0
29.0
81.4
30.7
75.5
29.9
94.5
40.2
54.3
28.2
68.0
21.3
76.4
72.7
85.2
45.6
84.0
73.3
93.3
58.3
68.7
72.1
76.9
32.7
72.2
55.6
87.4
31.9
79.9
60.9
94.7
42.9
64.4
50.1
80.1
21.5
72.7
45.2
86.0
53.7
79.3
49.2
92.3
64.9
66.3
41.2
79.7
43.8
74.5
51.2
87.5
53.4
76.7
52.0
90.1
55.1
72.3
50.3
84.8
51.8
77.5
48.0
87.7
72.1
79.4
47.6
89.9
75.1
75.6
48.5
85.4
69.1
75.3
63.3
83.8
57.2
82.4
66.4
91.3
67.4
68.3
60.0
76.4
47.2
70.8
42.0
85.7
52.6
79.6
43.8
95.2
72.7
62.3
40.1
76.7
33.5
70.3
37.6
87.8
44.5
77.9
40.6
94.4
60.3
62.8
34.6
81.1
30.2
70.1
36.9
85.8
56.8
74.7
42.5
89.5
64.7
65.9
31.1
82.3
50.8
60.5
31.6
77.9
29.5
67.5
35.5
84.9
38.8
53.7
27.5
71.0
22.0
70.0
30.4
88.8
51.3
73.6
34.6
90.6
63.6
66.6
26.0
87.2
42.0
69.3
39.0
86.3
47.8
74.3
45.3
89.7
56.6
64.7
32.4
83.0
41.2
58.6
56.8
66.0
32.9
79.9
59.1
93.8
54.2
36.8
54.4
37.5
12.9
63.8
36.2
81.5
29.9
69.8
40.4
87.2
39.3
57.9
31.9
75.8
21.8
70.1
41.5
89.4
29.1
76.8
45.4
94.1
48.9
63.4
37.5
84.6
12.7
67.3
34.0
87.6
24.2
72.0
38.5
90.7
34.0
62.5
29.1
84.4
15.1
69.6
45.8
83.4
42.7
77.5
49.4
91.9
53.5
61.6
42.1
74.9
32.6
70.4
48.2
83.5
44.2
78.7
51.7
92.5
54.8
62.1
44.7
74.4
34.0
69.1
44.9
83.2
40.4
77.8
48.6
92.8
51.3
60.3
41.2
73.6
29.9
65.4
36.2
83.1
34.5
71.7
40.2
88.9
45.9
59.2
32.0
77.4
24.8
Source: EPC and European Commission (2005a)
Table 2-6 Projected changes in participation rates up to 2050 used in the baseline
scenario
Total
Country
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
Male
Female
Total
Young
Prime age
Older
Total
Young
Prime age
Older
Total
Young
Prime age
Older
(15-64)
(15-24)
(25-54)
(55-64)
(15-64)
(15-24)
(25-54)
(55-64)
(15-64)
(15-24)
(25-54)
(55-64)
5.0
1.7
6.3
16.0
1.6
1.7
3.3
7.9
8.5
1.5
9.3
23.8
2.1
3.0
1.9
6.2
1.8
4.5
1.7
4.0
2.2
1.3
2.0
8.3
6.4
2.0
3.6
24.0
5.4
2.6
2.3
22.8
7.5
1.3
5.1
25.2
4.6
-1.4
5.3
10.2
-0.1
-1.8
0.4
0.0
9.2
-1.0
10.2
18.8
9.2
-2.6
10.3
20.3
3.1
-2.1
3.6
7.2
15.3
-3.1
16.9
32.2
3.8
0.9
3.8
15.8
2.0
0.5
1.6
14.1
5.3
1.3
5.7
17.5
8.4
-0.3
7.7
19.4
3.9
-0.4
3.5
6.1
12.8
-0.3
11.8
33.1
7.4
-0.8
6.3
24.8
4.3
-0.7
2.5
21.9
10.2
-0.9
9.7
26.8
3.4
0.0
6.7
11.4
-0.7
0.8
2.1
6.6
7.5
-0.8
11.4
16.3
4.0
1.0
5.3
10.5
-0.8
0.7
-0.2
2.7
9.0
1.3
10.9
18.4
6.9
1.6
5.1
27.3
3.9
1.0
1.4
24.0
9.8
2.3
8.7
30.1
5.0
-1.2
5.1
12.5
1.9
-0.5
1.7
5.6
7.8
-1.9
8.2
18.2
5.1
1.3
4.7
14.1
4.8
0.9
4.4
14.4
5.3
1.8
5.0
13.7
3.6
3.7
3.5
6.9
3.3
3.0
2.9
7.4
3.9
4.4
4.0
6.3
3.0
1.9
3.2
8.1
0.1
1.7
0.5
1.1
5.7
2.1
5.5
14.7
9.9
5.1
8.6
18.0
6.5
5.8
2.0
11.8
13.0
4.3
14.6
22.8
4.2
-0.8
2.8
15.6
1.9
-1.1
0.6
9.1
6.4
-0.5
5.2
20.8
6.0
2.0
5.5
7.0
5.2
2.4
5.3
1.4
6.5
1.6
5.3
10.9
5.9
0.1
4.6
20.6
4.0
0.2
3.3
15.8
7.5
0.1
5.8
23.9
7.1
2.3
4.6
17.1
6.4
-0.2
4.2
12.8
7.6
4.8
4.9
19.3
7.4
3.5
6.6
12.7
7.5
3.6
7.3
10.0
7.2
3.3
5.7
14.1
7.4
2.6
13.9
0.9
0.2
0.4
2.9
-2.2
15.0
4.8
25.7
2.9
7.2
3.0
8.2
19.4
6.6
2.8
5.6
20.6
7.8
3.2
10.6
17.2
3.8
0.7
3.4
22.9
1.9
-0.1
1.8
12.2
5.6
1.4
4.9
30.8
6.1
-2.6
4.7
28.8
4.4
-3.8
4.0
23.8
7.9
-1.2
5.5
33.2
5.9
2.2
5.3
17.7
3.3
2.0
2.3
13.2
8.4
2.3
8.1
21.6
5.7
1.4
5.1
17.8
2.8
1.3
1.9
12.9
8.5
1.4
8.2
22.2
6.2
0.7
5.6
20.1
3.2
0.7
2.2
15.5
9.1
0.6
8.9
24.3
6.4
1.7
6.2
18.3
5.1
1.3
4.2
16.0
7.4
2.1
8.1
19.3
Source: EPC and European Commission (2005a
37
… but labour supply will decline because of population trends
The size of the overall labour force (age 15-64) in the EU25 is estimated to increase by 5%
from 2003 to 2025 (see Graph 2-6). This is a result of combining the projected population and
rates of participation in each gender/age group. This translates into an increase in the labour
force of roughly 10.5 million persons. The increase is mainly due to the rise in female labour
supply, while the male labour force is projected to remain largely unchanged (only about 2
million additional people). However, this positive trend in female labour supply is projected
to reverse during the period 2025-2050 and along with the drop in male supply, the overall
labour force is expected to decrease by as much as 12% (equivalent to around 27.5 million
people, 16.5 million if compared with the level in 2003) although there are wide differences
across countries.
Graph 2-6 Baseline labour force projection (change in % of people aged 15-64 between
2003 and 2050)
2003-2025
2025-2050
% changes
50
40
30
20
10
0
-10
-20
SK
CZ
ES
PL
Nms10
GR
LT
PT
LV
SI
HU
IT
EE
DE
Eurozone
AT
EU25
EU15
FI
BE
DK
UK
NL
FR
CY
IE
SE
MT
LU
-30
Source: EPC and European Commission (2005a)
2.2.3.
Assumptions on unemployment
To move from labour force projections to employment projections, one should look at the rate
of unemployment. It was agreed that unemployment rates converge to their structural level, or
NAIRU (Commission estimates for the NAIRU as agreed upon in the Output Gap Working
Group of the EPC) by 2008 and that they remain constant thereafter. The following
adjustments are made to this general rule:
• countries with a NAIRU rate in 2008 higher than the average rate of the EU15 had their
unemployment rates further reduced so as to converge to the 2008 EU15 average (7%) by
2015;
• the EU10 countries with a NAIRU above the EU15 average (i.e. PL and SK) have 20 years
for their unemployment rates to converge to the EU15 average;
38
• to avoid significant changes in the rankings across countries, the structural unemployment
rate is reduced by an additional 0.5 percentage points (to reach 6.5%in 2015) for Belgium,
the Czech Republic and Italy.
The outcome of these assumptions is presented in Table 2-7. In aggregate terms,
unemployment rates in the EU25 are assumed to fall from 9.3% in 2003 to 7.8% in 2010 and
to 6.1% by 2025. A much bigger fall is projected for the EU10 countries, from 14.8% in 2003
to 12% in 2010. The approach to making assumptions results in large projected falls in
countries with the highest unemployment rates in the base year of 2003, i.e. a fall of over 10
percentage points in Poland and Slovakia, and of 4.6 percentage points in Spain.
Table 2-7 Assumptions on unemployment rates
2003
2010
2015
2025
2050
Change
2003-2025
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
8.2
5.5
9.9
9.8
11.6
9.0
4.8
8.9
3.7
3.7
4.3
6.7
9.2
5.7
5.1
4.4
7.9
10.3
5.9
12.5
10.7
7.6
20.1
17.6
6.8
9.3
8.2
9.0
14.8
7.0
4.3
8.5
8.6
8.7
8.3
3.4
7.3
4.2
3.2
3.4
5.6
6.8
4.3
4.6
4.2
7.3
7.8
4.8
8.9
7.6
8.3
15.8
15.2
5.5
7.8
7.0
7.6
12.0
6.5
4.3
7.0
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
12.9
12.5
5.5
6.7
6.1
6.5
10.0
Source: EPC and European Commission (2005a)
39
6.5
4.3
7.0
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
7.0
7.0
5.5
6.1
6.1
6.5
6.6
6.5
4.3
7.0
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
7.0
7.0
5.5
6.1
6.0
6.4
6.6
-1.7
-1.2
-2.9
-2.8
-4.6
-2.0
-1.4
-2.4
0.6
-0.5
-0.9
-1.1
-2.7
-1.4
-0.5
-0.2
-1.4
-3.3
-1.2
-5.5
-3.7
-0.6
-13.1
-10.6
-1.2
-3.1
-2.2
-2.5
-8.3
2.2.4.
Employment rate projections
A breakdown of employment rates by age and gender
Graph 2-7 shows the projected employment rates relative to the various Lisbon employment
targets. 28 The projected change in employment rates is due to the following developments:29
•
young persons (15-24): the projections were made by extrapolating forward the trends
observed in the past 5 years. Whilst in many countries (especially EU10) employment
rates of young persons have been falling, it has risen in some EU15 countries. This is
linked to more persons completing secondary education and higher enrolment in
tertiary studies;
•
women: the projections show female employment rates rising from just over 55% in
2004 to almost 65% by 2025 and remaining stable thereafter. This increase, which
would imply that the 60% Lisbon employment target is reached in 2010, is attributable
to the gradual replacement of older women with low participation rates by younger
women who have a much stronger attachment to the labour force. A trend of rising
employment rates of women has been observed for several decades, and is largely
explained by higher educational attainment and socio-cultural factors on the role of
women in the society. Whether the projected increases in female employment rates
materialise in practice may in part depend on supportive public policies or collective
agreements being put in place. For example, policies to promote access to affordable
childcare, the reconciliation between professional and private lives and to better
achieve gender equality could be important in this regard.30 Moreover, a rise in female
participation may have an impact on fertility rates and working hours, although the
magnitude of such effects and the sense of causality remain very uncertain;
•
older workers (55-64): the employment rate of older workers is projected to increase
sharply by 19 p.p. from 40% in 2004 for the EU25 to 47% by 2010 and 59% in 2025:
this is well in excess of the 50% Lisbon target that is projected to be reached by 2013.
The projection reflects the observed increase in employment rates of older workers in
recent years (up by 4.4 p.p. since 2000). It also incorporates the expected (albeit
uncertain) positive effects of enacted pension reforms. These reforms have, inter alia,
curtailed access to early retirement schemes, raised statutory retirement ages
(including minimum ages when pension income can be drawn) and strengthened
financial incentives to remain in the labour force. Note, the increase in the
employment rates for males (by 15 p.p. from 50% to 65%) is less than the projected
increase for females (23 p.p. from 30% to 53%). The difference arises due to a
stronger cohort effect for females. The increase in the participation rate due to
pensions is some 10 p.p. for both male and females, whereas the cohort effect for
females is almost 13 p.p. compared with 6 p.p. for males.
28
The Lisbon European Council (March 2000) Heads of State and Government set targets of raising the overall EU15
employment rate at 70% and 60% for women. The Stockholm European Council (March 2001) added two intermediate and
one additional target: the employment rate should be raised to 67% overall by 2005, 57% for women by 2005 and 50% for
older workers by 2010.
29
30
The analysis below is based on Carone (2005).
See chapter 3 in European Commission (2004a).
40
Graph 2-7 Projected employment rates and Lisbon targets in the EU25
2050 (p)
2020 (p)
2010 (p)
2004
Older workers
2000
2050 (p)
2020 (p)
2010 (p)
2004
Female
2000
2050 (p)
2020 (p)
2010 (p)
2000
2004
Total
Lisbon target
75
70
65
60
55
50
45
40
35
30
Note:
(p) means projected figures, while 2000 and 2004 figures are the actual ones.
Source: ECFIN calculations based on EPC and European Commission (2005a).
Given the population projections, the unemployment rate assumptions and the labour force
projections, the overall employment rate (age 15-64) in the EU25 is projected to increase from
63% in 2003 to 70% in 2025, and to stabilise at 70.7% at the end of the projection period, see
Table 2-7. The female employment rate is projected to increase by some 10 percentage points
to 65.5% by 2050, above the Lisbon employment target of 60%. The employment rate of
older workers is projected to increase by some 18 percentage points over the projection period
to 60.4% in 2050, and the Lisbon employment target of 50% is projected to be reached by
2013.
41
Table 2-8 Projected employments rates used in the 2005 EPC budgetary projection
exercise
Total (15-64)
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
2003
59.6
74.9
65.4
58.9
59.7
63.1
65.5
57.2
62.6
73.6
69.1
67.8
67.7
73.1
71.5
67.7
64.8
62.9
56.9
61.2
61.9
54.1
51.0
57.8
62.8
63.1
64.6
62.9
55.7
2010
62.1
76.4
70.9
62.7
66.4
64.4
70.9
61.0
64.4
75.3
73.5
71.9
70.2
74.9
72.9
73.6
66.8
68.4
60.8
67.3
69.9
56.7
57.0
62.1
67.7
66.9
68.1
66.9
60.7
2025
64.7
77.3
73.2
64.9
70.3
66.7
73.6
63.6
64.9
76.5
75.1
72.9
73.8
77.4
74.2
78.2
72.1
71.9
65.3
73.4
73.1
62.4
68.4
72.7
69.9
70.3
70.5
69.4
69.4
Females (15-64)
2050
65.5
77.9
73.5
65.1
71.4
68.0
74.6
65.7
65.4
77.9
76.4
73.4
74.4
77.6
74.7
77.3
69.7
70.8
63.2
71.7
71.4
61.3
66.1
68.7
69.3
70.9
71.5
70.5
67.1
2003
51.8
70.2
59.3
44.6
46.2
57.0
55.7
44.9
51.7
66.0
61.7
61.2
65.8
71.6
65.3
59.3
56.6
59.3
50.7
58.4
57.8
33.7
45.8
52.2
58.0
55.4
56.5
54.1
50.0
2010
56.0
72.0
65.8
50.0
55.6
58.9
62.7
50.0
55.6
70.1
67.8
66.4
67.9
73.5
67.3
67.0
59.8
64.7
54.2
64.6
65.3
39.6
51.8
56.9
62.5
60.2
61.2
59.4
55.2
2025
60.3
72.7
67.8
54.6
62.5
61.8
67.7
53.9
58.1
73.4
70.5
68.7
71.9
76.1
70.0
72.8
66.5
68.9
60.3
71.3
69.1
49.0
64.3
68.9
65.9
64.7
64.6
63.1
65.0
Older workers(55-64)
2050
61.0
73.3
68.3
55.6
64.2
63.4
69.1
56.1
58.7
75.2
71.8
69.5
72.7
76.4
71.1
72.0
63.8
67.4
58.6
69.0
66.7
48.6
60.9
64.3
66.4
65.5
66.1
64.6
62.1
2003
28.1
59.8
39.5
42.1
40.6
36.3
48.8
29.4
30.3
44.4
30.1
51.4
49.4
68.8
55.4
50.2
42.5
52.7
28.7
45.3
44.1
32.0
26.7
25.2
23.5
39.9
41.4
37.4
31.7
2010
33.2
61.5
56.4
44.4
45.6
42.3
55.5
35.9
35.3
48.1
40.1
56.5
54.1
70.9
56.9
60.7
48.1
55.3
39.6
53.1
53.4
29.3
35.2
38.5
40.4
47.1
48.6
46.0
39.8
2025
42.8
65.6
65.8
51.9
59.6
49.4
66.8
49.4
40.2
53.5
54.2
63.0
62.3
75.1
62.5
65.2
59.8
61.7
49.8
65.1
59.2
30.3
42.7
51.7
50.0
56.8
58.0
56.5
49.2
2050
44.4
66.7
65.7
52.9
62.5
52.9
68.9
54.6
41.8
55.2
58.0
64.7
64.9
76.6
63.9
69.1
58.9
61.7
49.5
66.2
58.7
33.1
48.7
51.2
52.6
58.9
60.2
58.8
51.9
Source: EPC and European Commission (2005a)
As shown on Table 2-9 the number of persons employed (according to the European Labour
Force Survey definition) is expected to record a positive annual growth rate of only 0.4% over
the period 2003-2025, and then reverse to a larger negative annual growth rate of about -0.5%
in the subsequent period (2025-2050). As a result, the overall number of people employed in
the EU25 in 2050 is projected to be about 9 million below the level recorded in 2003 (a drop
of 600,000 women and 8.2 million of men).
42
Table 2-9 Projected changes in employment (aged 15-64)
Changes
Annual
Growth rate
(thousands)
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
(as %)
2003-2025
2025-2050
2003-2050
2003-2025
2025-2050
2003-2050
2003-2025
2025-2050
315
-249
66
7.8
-5.7
1.6
0.3
-0.2
23
-151
-129
0.8
-5.6
-4.8
0.0
-0.2
1887
-5260
-3373
5.2
-13.7
-9.3
0.2
-0.6
331
-908
-577
7.5
-19.2
-13.1
0.3
-0.8
3906
-4552
-646
22.9
-21.7
-3.8
0.9
-1.0
1664
-694
969
6.8
-2.7
4.0
0.3
-0.1
604
-5
599
34.3
-0.2
34.0
1.3
0.0
1348
-3985
-2637
6.2
-17.1
-12.0
0.3
-0.7
41
28
69
21.7
12.4
36.8
0.9
0.5
381
-212
168
4.7
-2.5
2.1
0.2
-0.1
304
-502
-198
8.0
-12.3
-5.2
0.4
-0.5
218
-940
-722
4.6
-18.9
-15.2
0.2
-0.8
-0.2
28
-141
-112
1.2
-5.9
-4.8
0.1
353
107
460
8.3
2.3
10.9
0.4
0.1
1972
-1625
347
7.1
-5.4
1.2
0.3
-0.2
132
-1
131
40.5
-0.3
40.1
1.6
0.0
-126
-1034
-1160
-2.7
-22.8
-24.9
-0.1
-1.0
-14
-87
-101
-2.4
-15.6
-17.6
-0.1
-0.7
35
-713
-678
0.9
-17.9
-17.1
0.0
-0.8
92
-281
-189
6.5
-18.6
-13.3
0.3
-0.8
-14
-179
-193
-1.5
-18.5
-19.7
-0.1
-0.8
37
5
42
25.3
2.7
28.7
1.0
0.1
2698
-3404
-705
20.0
-21.0
-5.2
0.8
-0.9
369
-672
-303
16.9
-26.3
-13.9
0.7
-1.2
18
-159
-141
2.1
-17.8
-16.1
0.1
-0.8
16603
-25615
-9012
8.6
-12.2
-4.7
0.4
-0.5
13376
-19090
-5714
8.2
-10.8
-3.5
0.4
-0.5
11028
-17420
-6392
8.5
-12.4
-4.9
0.4
-0.5
3227
-6525
-3298
11.3
-20.5
-11.5
0.5
-0.9
Source: EPC and European Commission (2005a).
The broad trends described above are common to many countries, but they are not uniform
and the geographical patterns are striking. As shown in Graph 2-8, five smaller Member
States (CY, IE, LU, SE, MT) are projected to experience a pronounced rise in employment
between 2003 and 2050, while the change in employment in four EU15 Member States (FR,
NL, BE and UK) is projected to be slightly positive or stable. Eleven Member States are
projected to see falls in employment that are well above the average for the EU25 of -4.6%
(DE, GR, IT, PT, CZ, EE, HU, LT, LV, SK, SI).
43
Graph 2-8 Projected changes in employment (% change of employed people aged 15-64
between 2003 and 2050)
50
40
30
20
10
0
-10
Czech Republic
Latvia
Estonia
Hungary
Slovenia
Portugal
Slovak Republic
Greece
Lithuania
Italy
EU10
Austria
Germany
Poland
Denmark
Finland
EU25
Spain
EU15
Belgium
Netherlands
France
Sweden
Malta
Ireland
Luxembourg
Cyprus
-30
United Kingdom
-20
Source: EPC and European Commission (2005a)
2.2.5.
A closer look at the impact of ageing on labour supply and employment
The projected increases in the employment rates of women and older workers will, as
illustrated in Graph 2-9, temporarily cushion the effects of ageing on the labour force. Three
distinct time periods can be observed (with Table 2-10 below providing more information on
the peaks and troughs as regards the size of the working age population and the numbers of
persons employed per Member State):
•
2004-2011 – window of opportunity when both demographic and employment
developments are supportive of growth: both the working-age population and the
number of persons employed increase during this period. However, the rate of increase
slows down, as the effects of an ageing population take hold even if not yet visible in
aggregate terms. This period can be viewed as a window of opportunity, since both
demographics and labour force trends are supportive of growth. Conditions for
pursuing structural reforms may be relatively more favourable than in subsequent
years;
•
2012-2017 – rising employment rates offset the decline in the working-age population:
during this period, the working-age population will start to decline as the baby-boom
generation enter retirement. However, the continued projected increase in the
employment rates of women and older worker will cushion the demographic factors,
and the overall number of persons employed will continue to increase albeit at a
slower pace. This period could be characterised by tightening labour market
conditions with potentially growing mismatches and the risk of heightened wage
pressures. The window of opportunity will be closing rapidly;
•
the ageing effect dominates from 2018: the trend increase in female employment rates
will broadly have worked itself through by 2017. In the absence of further pension
reforms, the employment rate of older workers is also projected to reach a steady state.
Consequently, there is no counter-balancing factor to ageing, and thus both the size of
the working-age population and the number of persons employed both enter a
downward trajectory.
44
Graph 2-9 Projected working-age population and total employment, EU25
total employment
w orking-age population
employment rate (right scale)
72
320
300
280
p erio d 2 0 0 3 -2 0 11:
rising emp lo yment
b ut slo w g ro wt h in
wo rking -ag e
260
p o p ulat io n
240
220
70
68
p erio d 2 0 12 2 0 17:
rising
emp lo yment
d esp it e t he
d ecline in
wo rking -ag e
f ro m 2 0 18 o nward :
66
emp lo yment and wo rking -ag e p o p ulat io n b o t h d eclining
64
62
200
60
180
58
2003
2008
2013
2018
2023
2028
2033
2038
2043
2048
Source: DG ECFIN and the EPC
Table 2-10-Peaks and troughs for the size of the working-age population and the total
number of persons employed (aged 15-64)
Working-age population (15-64)
% change
% change
peakpeak year
2003-peak
trough
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
2011
2008
2003
2010
2010
2011
2035
2004
2050
2011
2012
2008
2010
2050
2011
2043
2007
2006
2003
2006
2003
2041
2011
2010
2011
2011
2011
2011
2009
2.9
0.7
0.0
1.2
6.3
3.3
23.1
0.7
30.9
2.5
2.3
1.6
1.3
4.3
3.8
26.3
0.8
0.2
0.0
0.1
0.0
14.5
2.4
2.7
0.9
1.9
2.1
1.7
1.3
-10.0
-9.8
-19.2
-22.2
-24.3
-6.6
-4.4
-23.9
-7.2
-16.2
-22.7
-14.5
-6.7
-2.9
-30.7
-26.9
-25.4
-26.1
-30.3
-0.8
-28.6
-29.5
-24.7
-16.7
-14.6
-16.6
-27.5
Employment (15-64)
peak year
% change
2003-peak
% change
peak-trough
2017
2009
2015
2015
2020
2015
2035
2018
2050
2019
2019
2013
2011
2050
2018
2041
2013
2011
2011
2016
2012
2037
2025
2020
2012
2017
2017
2016
2015
10.3
2.4
10.7
10.8
24.1
7.3
39.8
8.6
36.8
6.0
11.1
7.9
5.3
10.9
7.8
44.2
3.4
7.2
5.5
12.7
10.5
29.8
20.0
17.4
9.0
10.6
10.2
11.0
13.1
-7.8
-8.1
-18.0
-21.6
-22.5
-3.1
-4.1
-19.0
-4.8
-14.7
-21.4
-9.6
-6.1
-2.8
-27.3
-23.1
-21.5
-23.1
-27.3
-0.9
-21.0
-26.6
-23.0
-13.8
-12.4
-14.3
-21.8
Note: The trough for the size of the working-age population is 2050 for all countries except DK (2044) and NL
(2039). Trough for number of persons employed is 2050 for all countries except DK (2041) and NL (2041).
Source: DG ECFIN calculations based on EPC and European Commission (2005a).
45
2.3.
Labour productivity and potential growth rates31
Assumptions on productivity based on a ‘production function approach’
It has been agreed to use a ‘production function approach’ to estimate labour productivity
growth. Labour productivity (output per worker) is derived from the calculations based on the
labour input projections, the assumptions concerning Total Factor Productivity (TFP) and the
investment scenario. This approach aims at shedding light on the reasons behind productivity
developments and obtaining a richer medium-term dynamic including the effect of population
growth on labour productivity in the medium run through the change in capital intensity.
As explained in EPC and European Commission (2005a), the following assumptions have
been agreed:
• to take the scenario of the Output Gap Working Group (OGWG) over the medium run
(2007-2009) while sorting out the level differences between the OGWG and (cohortapproach-based) AWG labour input series;
• for the EU15 countries, the growth rate of Total Factor Productivity (TFP) will converge to
1.1% (i.e. the US trend labour productivity growth) by 2030, with different speeds of
convergence across Member States32. For the EU10, TFP will converge to 1.75% by 2030
and thereafter converge at the same pace so as to reach 1.1% in 2050;
• in order to allow for a faster convergence across the EU10 Member States, three quarters
of the convergence towards 1.75% and 1.1% is achieved in 2015 and 2035, respectively.
Indeed, while a longer period of convergence (by 2050) is necessary for the EU10 Member
States, there is a clear need for countries to converge to the same growth of output per
worker at the end of the projection horizon;
• as regards the capital deepening assumptions, the EPC agreed to hold the investment/ GDP
ratio constant until 2010 in the baseline scenario. A transition to a constant capital/ labour33
ratio assumption is introduced gradually (in a linear manner) over the period 2010 to 2030.
Finally, the capital/labour ratio expressed in efficiency units (capital per effective worker)
is held constant from 2030 to 2050. This implies that both the capital stock per worker and
labour productivity grows at the same pace, which coincides with labour-augmenting
technical progress (i.e. TFP growth - equal to 1.1- divided by the labour share, set equal to
0.65).
Projection results for potential GDP growth in the baseline scenario
By combining the employment and productivity projections, a projection for potential GDP
growth rates up to 2050 is obtained. Table 2-11 presents the outcome of these assumptions in
31
A more detailed description of the approach used to make the assumptions and projections on labour productivity and
GDP growth can be found in Carone G., C.Denis, K. Mc Morrow, G. Mourre, W. Röger (2006), forthcoming.
32
Some countries underwent specific adjustments in their TFP profile in the period 2010-2030 such as GR, IT, PT and ES,
in order to allow for stronger real convergence in productivity level.
33
Labour here refers to technical-progress-augmented labour (i.e. labour measured by efficiency unit).
46
terms of the projections for potential growth rates up to 2050 as well as its determinants. For
the EU25, the annual average potential GDP growth rate in the period 2004 to 2010 is
projected to decline from 2.4% to 1.2% in the period 2031-2050. The projected fall in
potential growth rates is much higher in the EU10. For the EU10, potential GDP growth rates
of 4.5% between 2004 and 2010 are projected to fall to 0.9% between 2031 and 2050. This
occurs in part because the productivity growth rates between the EU10 and EU15 are assumed
to have converged by then, but especially because of their less favourable demographic
projections.
Table 2-11 Projected potential growth rates and determinants
Potential Growth
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
Labour productivity
Employment
2004-2010
2011-30
2031-50
2004-2010
2011-30
2031-50
2004-2010
2011-30
2031-50
2.4
2.0
1.7
2.9
3.0
2.2
5.5
1.9
4.0
1.7
2.2
1.9
2.7
2.7
2.8
4.3
3.5
6.1
3.7
6.5
7.7
2.2
4.6
4.6
3.7
2.4
2.2
2.1
4.5
1.8
1.6
1.4
1.6
2.0
1.8
3.3
1.5
3.0
1.6
1.6
2.1
1.7
2.4
2.1
3.5
2.6
3.0
2.6
3.3
3.4
2.8
3.2
3.4
2.5
1.9
1.8
1.7
3.0
1.5
1.6
1.2
0.8
0.6
1.6
1.6
0.9
3.0
1.7
1.2
0.8
1.5
1.8
1.5
1.9
0.8
1.2
1.1
1.1
1.1
2.0
0.9
0.6
1.1
1.2
1.3
1.2
0.9
1.5
1.9
0.9
2.1
1.1
1.4
3.4
0.7
1.8
1.1
1.5
1.2
2.1
2.2
2.1
2.4
3.4
5.3
3.2
5.7
6.5
1.0
3.8
3.9
3.3
1.5
1.3
1.1
3.6
1.8
1.8
1.6
1.8
1.9
1.7
2.5
1.7
1.9
1.7
1.8
2.4
2.0
2.3
2.1
2.9
3.0
3.6
2.9
3.6
4.1
2.2
3.1
3.3
3.0
2.0
1.8
1.8
3.1
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.7
1.7
1.7
1.9
0.9
0.1
0.8
0.9
1.9
0.8
2.0
1.1
2.2
0.6
0.7
0.7
0.6
0.6
0.7
1.9
0.1
0.7
0.5
0.8
1.2
1.2
0.7
0.7
0.4
0.9
0.9
1.0
0.9
0.0
-0.2
-0.3
-0.2
0.1
0.1
0.8
-0.2
1.0
-0.1
-0.2
-0.3
-0.3
0.1
0.0
0.6
-0.4
-0.6
-0.3
-0.4
-0.7
0.6
0.1
0.1
-0.5
-0.1
-0.1
-0.1
-0.1
-0.2
-0.1
-0.5
-0.9
-1.1
-0.1
-0.1
-0.8
1.3
0.0
-0.5
-0.9
-0.2
0.1
-0.2
0.0
-1.1
-0.7
-0.9
-0.8
-0.8
0.0
-1.1
-1.3
-0.8
-0.5
-0.4
-0.5
-1.0
Source: EPC and European Commission (2005a)
The projected potential GDP growth rates for all countries are shown in Graph 2-10. Almost
all countries are projected to experience a steady decline. It will become apparent as of 2010,
and will be most significant in countries with the highest starting point, notably the EU10. In
many countries, potential annual growth rates will have dropped to close to, or below, 1%
during the period 2030 to 2050. Only a few small countries (LU, LV, CY, IE, LT, and EE) are
projected to enjoy an average growth rate higher than 2.5%, while a few larger countries (DE,
GR, IT and PT) are expected to grow at a rate lower than 1.5% over the whole period.
47
Graph 2-10 Projected potential GDP growth (annual average) in the EU25 Member
States
2004-2010
2011-2030
2031-2050
8
7
6
5
4
3
2
1
0
EU15
Source: EPC and European Commission (2005a)
EU10
The sources of economic growth are also projected to change
In addition to falling potential GDP growth rates, the sources of growth will alter
dramatically. Employment will make a positive contribution to growth in both the EU15 and
the EU10 up to 2010, but becomes neutral in the period 2011-2030 and turn significantly
negative thereafter. Over time, productivity will become the dominant source of growth.
Graph 2-11 Projected (annual average) potential growth rates in the EU15 and EU10
and their determinants (employment/productivity)
4.0
4.0
4.0
4.0
3.0
3.0
3.0
3.0
2.0
2.0
2.0
2.0
1.0
1.0
1.0
1.0
0.0
0.0
0.0
0.0
-1.0
-1.0
-1.0
2004-10
Labour productivity growth
GDP growth
S i 14
2011-30
2031-50
L a b o u r p ro d u c t iv it y g ro w t h a n d
E m p lo y m e n t g ro w t h
5.0
G D P g ro w th
L ab o u r p ro d u c tiv ity g ro w th a n d
Em p lo y m e n t g ro w t h
EU10
5.0
-1.0
2004-10
Employment growth
GDP per capita growth
S i 15
5.0
2011-30
Labour productivity growth
GDP growth
2031-50
Employment growth
GDP per capita growth
Source: EPC and European Commission (2005a)
In order to assess the relative contribution to GDP growth of its two main components, labour
productivity and labour utilisation, Table 2-12 uses the standard accounting framework. One
can see the compensating effects of an increasing employment rate (which on average
contributes 0.2 percentage points to average GDP growth over the projection period) and a
48
G D P g ro w t h
EU15
5.0
decline in the share of the working-age population (which is a negative drag on growth by an
average of -0.3 percentage points).
Table 2-12 GDP growth and its sources, 2004-2050
AVERAGE 2004-2050
GDP growth
EU25
EU15
Euro area
EU10
1.7
1.6
1.5
2.4
1.8
1.7
1.6
2.7
1.2
0.6
-0.1
1.1
0.6
-0.1
1.1
0.6
-0.1
1.6
1.1
-0.3
due to % change in:
Productivity (GDP/per employee)
of which :
Total factor productivity
Capital deepening
Labour utilisation
of which :
Employment rate
0.2
0.2
0.3
0.4
Share of working age population
-0.3
-0.3
-0.4
-0.4
Population
0.00
0.04
0.01
-0.27
Note: The level of GDP is given by the product of labour productivity (GDP per hour worked) by the different
components of labour utilisation (average hours worked per person, the employment rate and the share
of working-age population) and the population. GDP growth is (roughly) equivalent to the sum of the
growth rates of these variables.
Source: DG ECFIN calculations based on EPC and European Commission (2005a).
Developments in terms of GDP per capita
Table 2-13 presents the projections for GDP per capita growth rates and provides an
indication of GDP per capita and productivity levels relative to the average for the EU15. The
effects of an ageing population on living standards can more closely be observed by looking
at growth rates in terms of GDP per capita. As expected, the projected decline in GDP per
capita growth rates in both the EU15 and the EU10 is less than the projected fall in potential
output growth rates, since total population growth rates should drop over the period 20042050. Hence, living standards should hold up better than what is suggested by the trend in
headline GDP growth rate.34 It is also interesting to note from Table 2-13 that per capita
income levels in EU10 are projected to increase from 50% of EU15 average in 2004 to 78%
in 2050.
34
A further distinction worth noting is that the retirement of the baby-boom generation will lead to some
slowdown in GDP per capita growth in comparison with GDP per worker. To the extent that wages over the
long-run reflect developments in GDP per worker, a shift could occur in the relative income position of
different age cohorts.
49
Table 2-13 GDP per capita growth: growth rates and levels relative to EU15 average
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
Euro area
EU10
GDP per capita growth rates (%)
2004-10
2011-30
2031-50
2.1
1.6
1.6
1.8
1.5
1.7
1.6
1.4
1.5
2.6
1.6
1.1
2.0
1.9
0.9
1.7
1.5
1.6
4.2
2.5
1.2
1.6
1.6
1.3
3.1
2.1
2.4
1.3
1.3
1.7
1.9
1.5
1.4
1.5
2.1
1.1
2.4
1.6
1.7
2.3
2.0
1.7
2.4
1.8
1.5
2.9
2.7
1.6
3.6
2.8
1.3
6.6
3.5
1.6
3.9
2.8
1.4
7.0
3.7
1.5
8.3
3.9
1.5
1.3
2.2
1.7
4.7
3.4
1.3
4.7
3.6
1.0
3.6
2.5
1.4
2.2
1.8
1.4
1.9
1.7
1.4
1.8
1.6
1.4
4.6
3.2
1.3
GDP per capita (EU15=100)
2004
108
110
101
72
85
105
132
100
194
108
116
68
108
112
104
81
64
46
54
43
42
68
45
48
73
92
100
99
50
2030
107
107
94
72
90
101
177
97
226
98
113
73
110
123
111
107
89
86
76
86
93
73
75
83
94
97
100
97
80
2050
109
111
95
68
81
103
167
94
270
103
112
68
115
129
113
110
86
87
75
87
94
76
73
77
94
97
100
96
78
Productivity levels (EU15=100)
2004
122
98
94
84
91
113
128
116
129
93
109
60
104
104
95
77
59
46
61
46
42
80
54
52
71
93
100
101
56
2030
115
100
88
79
88
110
161
108
135
92
106
71
112
116
107
94
87
82
81
80
88
81
76
76
96
97
100
98
80
2050
115
100
88
79
88
110
161
108
135
92
106
71
112
116
107
97
90
86
85
84
92
84
79
80
100
98
100
98
83
Source: EPC and European Commission (2005a)
2.4.
Other macroeconomic assumptions
Real interest rates: the EPC agreed to assume a real interest rate of 3%.
Inflation: projections will be reported in 2004 prices. However, for technical reasons, some
countries may need to introduce an assumption on inflation into their models, and in this
event, the EPC agreed that it should be 2% for all countries.
Growth of real wages: it is assumed that real wages grow in line with labour productivity. As
a result, the wage share will remain constant over the projection period. The rule is applied to
all Member States uniformly.35
2.5.
Some overall conclusions on economic impact of ageing
Significant policy challenges lie ahead
The projection results described above suggest that ageing populations will have a significant
impact on Europe’s economies in the decades ahead. From an economic perspective, potential
35
The assumption is well-founded in economic theory. If the real wage is equal to the marginal productivity of labour, it follows that under
the standard features of the production function, real wage growth is equal to labour productivity growth and real unit labour costs remain
constant.
50
growth rates will fall to levels below those observed in recent decades: however, living
standards as measured by GDP per capita should hold up better than what is suggested by the
trend in headline GDP growth rate. Pressure for increased public spending will result from
having a higher share of the total population in older age cohorts that receive larger public
transfers (e.g. pensions) and services (health care, long-term care). The financing side may
also be affected, with a decline in the support ratio of contributors to beneficiaries.
These developments can best be viewed by comparing the projected demographic dependency
ratios (that emerge from the AWG population scenario) with the economic dependency ratios
(that result from the employment and GDP projections), see Graph 2-12 and Table 2-14.
Over the next decades the old-age dependency ratio, that is the number of people aged 65
years and above, relative to those between 15 and 64, is projected to double, reaching 51% in
2050. This means in the EU, the current situation of having four people of working-age for
every elderly citizen change into a ratio of 2 to 1 (even higher in some countries). The
effective economic old-age dependency is also shown on Table 2-14, which is the number of
non-active persons aged 65 and above as a percentage of employed persons aged 15 to 64. As
expected, this ratio is higher than the old age-dependency ratio, and projected to rise sharply
for the EU25 from 37% in 2003 to 48% in 2025 and 70% in 2050, raising complex issues on
the role of public transfers in achieving an appropriate distribution of resources between a
smaller active population and a larger inactive retired population.
Graph 2-12 Projected demographic and economic dependency ratios for the EU 25
160
140
120
100
80
60
40
20
0
2005
2030
2050
change
old-age dependency ratio (65+ as share of population 15-64)
effective economic old-age dependency ratio (non active 65+ as % employed population 15-64)
total economic dependency ratio (total population less employed as % of employed population 15-64)
Source: EPC and European Commission (2005a)
The total economic dependency ratio measures the total inactive population (total population
less persons employed) as a percentage of persons employed (aged 15 to 64). It gives an
indication of the average number of people which each economically active person ‘supports’,
and thus is relevant when considering the prospects for potential GDP per capita growth. For
the EU 25, this ratio actually falls from 136% in 2003 to 125% in 2025, but thereafter
increases to 147% by 2050. The overall economic dependency is projected to decline up to
2025 mostly due to a better labour market performance (especially the projected trend
increase in female employment rates), but also due to low fertility (as smaller numbers of
51
young people imply a decline in the youth dependency ratio). However, these effects taper off
after 2025, and the increase in the total economic dependency ratio between 2025 and 2050 is
noticeably steeper.
Table 2-14 Projected changes in demographic and economic dependency ratios
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
Old-age dependency ratio
Effective economic old-age dependency ratio
Total economic dependency ratio
(population aged 65 and above as a percentage
of the population aged 15-64*)
(non active population aged 65 and above as
a percentage of employed population aged 15-64)
(total population less employed as a percentage
of employed population aged 15-64)
2003
2025
2050
26
22
26
26
25
25
16
28
21
20
23
23
23
26
24
14
20
23
22
22
23
19
18
16
21
24
25
19
36
34
38
36
33
37
25
39
28
33
34
35
41
36
33
29
35
31
34
29
31
34
33
28
36
35
36
33
47
42
52
60
66
46
45
62
36
41
52
59
47
41
45
43
55
43
48
45
44
41
51
51
56
51
52
50
change
2003-50
21
20
26
35
41
21
29
34
15
20
30
36
24
14
21
30
35
20
26
23
21
22
33
34
35
27
26
31
2003
2025
2050
43
28
39
41
40
39
23
49
33
27
33
30
33
35
32
18
29
35
39
35
35
34
35
28
32
37
38
34
55
42
50
52
45
53
31
60
42
41
45
43
54
45
42
35
47
41
51
38
39
54
46
38
49
48
49
45
71
52
69
88
88
66
56
93
55
51
67
73
60
50
57
52
76
57
74
60
58
66
74
73
77
70
70
73
change
2003-50
28
24
30
47
48
27
33
44
22
24
35
43
27
15
25
33
46
22
35
25
23
32
40
45
44
33
32
39
2003
2025
2050
156
101
127
150
144
144
125
162
138
101
113
118
121
111
113
120
119
135
156
144
137
170
183
146
127
136
132
159
150
106
117
141
118
146
108
149
137
107
108
116
128
113
114
96
116
118
140
107
113
154
127
105
124
125
126
124
164
116
135
181
162
156
132
179
149
114
128
149
133
117
128
114
154
137
172
134
137
168
163
151
157
147
145
158
change
2003-50
8
14
9
31
18
12
7
17
11
13
15
30
12
6
14
-6
35
2
16
-10
0
-2
-20
6
31
11
13
-1
Source: EPC and European Commission (2005a)
Some positive developments are underway, in part due to reforms already carried out.
There are some positive indications which emerge from the analysis:
•
first, employment rates and levels are projected to continue rising for at least a decade,
which will offset somewhat the projected decline in the size of the working-age
populations and provides a window of opportunity to undertake necessary reform
measures;
•
second, the projections confirm the validity of the Lisbon strategy. They already
embody the achievement of the overall Lisbon employment targets (although only
reached in 2020 for the EU25), but also confirm the importance of policies to raise
52
productivity potential. Higher levels of investment in physical and human capital
could yield substantial productivity gains over the long run, especially against a
background of a knowledge-based society. There is strong evidence that higher
educational attainment leads to enhanced labour productivity and adaptability to a
knowledge-based economy. The higher enrolment rates in second and third level
education observed in many countries, coupled with a greater focus on quality and
efficiency, may contribute to improved productivity in the future, albeit with a lag of
several years even decades. The interaction between labour- and product market
reforms is worth highlighting in this context, as more flexibility in these markets
facilitates resource re-allocation to more innovative and productive activities.
•
the projections illustrate the effects of successful structural reforms, and that policy
action can have a substantial impact on our capacity to meet the challenge of ageing.
The projections indicate that pension reforms already enacted by Member States,
could lead to a 10 percentage point increase in the employment rate of older workers,
thus reaching levels above the Lisbon employment targets.
53
3.
PENSIONS
3.1.
Introduction
This chapter presents the projection results for spending on pensions. It builds upon the 2001
projection exercise of the EPC, which in addition to being used in the assessment at EU level
of the sustainability of public finances, also fed into the open method of co-ordination on
pensions36. Considerable efforts have been made to improve upon the 2001 exercise in two
important respects:
• the coverage of pension schemes included in the exercise is more complete and
comparable. In the 2001 projection exercise, the coverage of early retirement and disability
pension schemes, as well as some specific schemes such as those covering public sector
employees, was incomplete;
• the decomposition of projection results has been improved. The 2001 projection results
lacked clarity and were not disaggregated, e.g. no breakdown of pension expenditure was
presented and old-age pensions could not be analysed separately.
The remainder of the chapter is structured as follows. The next section deals with the
coverage of the exercise. After briefly summarising the very different pension schemes that
exist in the EU Member States, a detailed description is provided of those pension schemes
included in this projection exercise. Section 3.3 presents the results for the baseline scenario.
Section 3.4 presents the results of the sensitivity tests.
3.2.
Pension schemes and their coverage in the projections
3.2.1.
Overview of the pension systems
Pension systems are very diverse in the EU Member States. However, all countries have a
strong public sector involvement in the pension system through their social security systems,
while the importance of occupational and private pension provisions varies. In most countries,
the core of the social security pension system is a statutory earnings-related old-age pension
scheme, either a common scheme for all employees or several parallel schemes in different
sectors or occupational groups. In addition, the social security pension system often provides
a minimum guaranteed pension to those who have not qualified for the earnings-related
scheme or have accrued only a small earnings-related pension. Usually, such minimum
guarantee pensions are means-tested and provided either by a specific minimum pension
scheme or through a general social assistance scheme. In a few Member States, notably in
Denmark, the Netherlands, Ireland and the United Kingdom, however, the social security
pension system provides in the first instance a flat-rate pension, which is supplemented by
earnings-related private occupational pension schemes (in the UK, also by a public earningsrelated pension scheme (State Second Pension) and in Ireland by an earnings-related pension
scheme for public sector employees). In these countries, the occupational pension provision is
36
Council of the European Union (2003), ‘Adequate and sustainable pensions. Joint Report by the
Commission and the Council’, 7165/03.
54
equivalent to the earnings-related social security pension schemes in most of the EU
countries.
A further source of diversity relates to the fact that a number of Member States, including
Sweden and a number of new Member States such as Estonia, Latvia, Lithuania, Hungary,
Poland and Slovakia, have switched a part of their social security pension schemes into
private funded schemes. Usually, this provision is statutory but the insurance policy is made
between the individual and the pension fund. Participation in a funded scheme is conditional
on participation in the public pension scheme and is mandatory for new entrants to the labour
market (in Sweden for all employees), while it is voluntary for older workers (in Lithuania it
is voluntary for all people).
According to the decision of EUROSTAT37, these schemes should be included in the private
sector in national accounts because the transactions are between the individual and the
pension fund. Thus, they are not recorded as government revenues or expenditure, and
consequently, they do not have an impact on the government surplus or deficit. In addition,
the insured persons have the ownership of the assets of the fund and, thus, they bear the risks
and enjoy the rewards regarding the value of the assets. Furthermore, the EUROSTAT
decision specifies that a possible government guarantee for such a fund is not an adequate
condition to classify such schemes as social security (public) schemes, because such a
guarantee is a contingent liability and these are not considered as economic transactions until
they materialise.
Social security pension systems diverge from each other as regards the type of benefits
provided by the pension system. Most pension schemes provide not only old-age pensions but
also early retirement pensions, disability and survivors’ pensions. Some countries, however,
have specific schemes for some of these benefit types, in particular, some countries do not
consider disability benefits as pensions, despite the fact that they are granted for long periods,
and may be covered by the sickness insurance scheme.
Furthermore, pension systems differ across countries regarding the financing method of the
schemes. Most social security schemes are financed on a pay-as-you-go (PAYG) basis,
indicating that the contribution revenues are used for the payments of current pensions. In
addition, there is a considerable variation between countries regarding the extent to which the
contribution revenues cover all pension expenditure. In most countries, minimum guarantee
pensions are covered by general taxes. However, it is also common that earnings-related
schemes are subsidised to varying degrees from general government funds or some specific
schemes (notably public sector employees’ pensions) do not constitute a clear scheme but,
instead, pensions appear directly as expenditure in the government budget. On the other hand,
some predominantly PAYG pension schemes (FI, LU, SE) have statutory requirements for
partial pre-funding and, in view of the increasing pension expenditure, many governments
have started to collect reserve funds for their public pension schemes. Occupational and
private pension schemes are usually funded. However, the degree of funding relative to the
pension promises may differ due to the fact that benefits can be defined either on the basis of
benefit rights linked to the salary and career length (defined-benefit principle) or of paid
contributions (defined-contribution principle).
37
Classification of funded pension schemes in the case of government responsibility and guarantee,
EUROSTAT 20/2004, 2 March 2004
55
Table 3-1 Overview of the pension systems in Member States
Social security pensions (public sector schemes)
Occupational pension schemes (private
sector schemes)
Individual (private) pension schemes
(private sector schemes)
BE
Minimum guarantee pensions:
Means-tested minimum pensions through social assistance (GRAPA-IGO)
Earnings-related social security pensions:
Separate schemes for private and public sector employees, self-employed; schemes
cover old-age and survivors’ pensions, and disability pensions in the case of civil
servants (which are included in public (social security) pensions in this report);
Disability pension schemes for private sector employees and self-employed.
Early retirement (“pre-pension”) through an unemployment benefit and a supplement
from the employer
Legal framework has been established. The
provision of occupational pensions is minor
(pensions accounted for 1.3% of GDP in
2004).
Voluntary private schemes exist only to a
minor extent
CZ
Minimum guarantee pensions: No special scheme, it is embedded in the pension
formula (flat-rate component)
Earnings-related social security pensions:
One scheme covering the whole population, also providing a flat-rate pension to
economically inactive persons; covering old-age, disability and survivors’ pensions;
Public security personnel (armed forces, police, custom officers, firemen) pensions
paid from the state budget.
DK
Minimum guarantee pensions:
Universal flat-rate pensions for every citizen (subject to the time lived in DK), meanstested supplements to those without occupational pensions, tax-financed;
Disability pensions to those below 65.
Earnings-related social security pensions:
Voluntary early retirement pensions (requires 25 years of contributions; pension
benefit dependent on age, not on contributions);
Civil servants’ pensions for central and local government employees (in coming years
these schemes are replaced by ordinary labour market (occupational) pensions.
DE
Minimum guarantee pensions: No special scheme but disabled and older people
without sufficient income are entitled to means-tested benefits (social assistance)
Earnings-related social security pensions:
General scheme covering private and public sector employees, the scheme covers oldage, disability, early retirement and widow’s pensions; specific schemes for life-time
civil servants as well as farmers and miners;
Do not exist
Labour market (occupational) pensions
(private sectorcovering 90% of the
employees),
Labour market supplementary pensions
(ATP),
Special pension savings plan (SP),
Labour market supplementary pensions for
recipients of anticipatory pensions (SAP)
Employees’ capital fund (LD);
All these schemes are fully funded.
Occupational pension provision existing;
benefits account for 1.3% of GDP; supported
by SSC exemptions up to 4% of SSC ceiling,
equal to 2472€ in 2004, and by tax exemption
up to 4300€.
In 2003, about 30% of newly retired received
occupational pensions.
In 2005, about 60% contribute to such
schemes (including private funded schemes,
about 70% of employees contribute to
supplementary schemes).
56
Voluntary private pension scheme at an early
accumulation stage; low replacement rate
(contribution 2.1% of wage; covers about
half labour force
Individual pension savings plans (1.1 million
contributors)
Individual funded pensions of growing
importance since the 2001 reform (supported
by tax exemptions and direct allowances;
contribution rate 2% of wages in 2004, to be
increased to 4% by 2008). Currently, about
4.7 mill. so-called Riester-contracts exist.
EE
Minimum guarantee pensions:
National pension equal to the base amount of the pension ins. scheme, available to
those not qualifying for insurance scheme.
Earnings-related social security pensions:
One scheme covering the whole population; covering old-age, disability and
survivors’ pensions; benefits are flat-rate + a length-of-service supplement for careers
before 1999, as of 1999 benefits are earnings-related
Do not exist
Statutory private schemes for the switched
part of the social security pension scheme,
mandatory for persons born 1983 or later and
voluntary for old persons; in 2005, over 50%
of workers had joined the funded scheme.
The switched contribution rate 4% + an
additional 2% contribution paid by the
insured person.
GR
Minimum guarantee pensions:
Means-tested minimum pensions through?
Earnings-related social security pensions:
A great number of separate pension insurance and auxiliary funds for different sectors
and occupational groups; schemes cover old-age, early retirement, disability and
survivors’ pensions; benefit levels differ across schemes
Minimum guarantee pensions:
Means-tested minimum pension scheme (non-contributory)
Earnings-related social security pensions:
One main social insurance scheme, covering the private sector employees, selfemployed and the regional and local public administrations, providing earnings-related
old-age, disability and survivors’ pensions;
Public sector employees’ (contributory) pension scheme (CPE) for the civil servants
of the central public administration and the military, providing mainly flat-rate oldage, disability and survivors’ pensions, though 5 different levels of pensions according
to the career level
Minimum guarantee pensions:
Means-tested minimum pension scheme;
Earnings-related social security pensions:
A great number of separate pension insurance schemes for different sectors and
occupational groups providing earnings-related pensions, additionally mandatory
‘second tier’ supplementary funds that complement the pension provision; schemes
cover old-age, early retirement and survivors’ pensions; benefit levels across insurance
schemes were aligned in the 2004 reform.
Disability pensions (benefits) covered by the health insurance scheme.
Minimum guarantee pensions:
Means-tested minimum flat-rate pensions and age-related benefits (old-age, widows,
disability and pre-retirement allowances) through non-contributory social assistance
scheme
Contributory social insurance pensions:
Contributory social insurance scheme provides flat-rate pensions and age-related
benefits (old-age, retirement, and widow(er)’s pensions, invalidity and disability
benefits)
Public service occupational pension scheme (benefits 1.1% of GDP in 2004).
Do not exist (legal framework has been
established but no scheme was operational yet
in 2004)
Voluntary private pension schemes cover
about 5% of the population.
Voluntary enterprise pension schemes for
private sector employees (funded DC
schemes);
Mandatory supplementary pension scheme for
public sector employees of the central
administration (funded DC scheme);
Schemes are of some importance.
Voluntary private schemes (funded DC
schemes);
Do not exist
Legal framework has been established and
some schemes have been introduced but they
are not yet operational)
Voluntary occupational schemes for private
sector employees. 33% of current pensioners
receive also occupational pensions, amounting
to 25% of total pension income. Contributor
coverage to occupational schemes is just over
half the employees.
Voluntary individual schemes also play a
role in the Irish pension system. In recent
years, a series of significant tax incentives
have been introduced for the purpose of
promoting pension provision amongst selfemployed, employers in non-pensionable
employment and proprietary directors.
ES
FR
IE
57
IT
Minimum guarantee pensions:
Means-tested social assistance pensions to those not qualifying for or not having
accrued the minimum level of earnings-related scheme
Earnings-related social security pensions:
One main social security pension scheme covering the whole population, providing
old-age, early retirement (seniority), disability and survivors’ pensions;
NDC scheme fully applied to persons entering the labour market as of 1996, transition
schemes for workers already in the labour market in 1995; old DB scheme applied to
the workers with at least 18 years of contributions at the end of 1995.
Voluntary supplementary funds exist. The
2004 reform increased the provisions for
occupational pensions through the possibility
to transform TFR (end-of-service allowance)
into an occupational pension scheme.
CY
Minimum guarantee pensions:
Through Social ( means-tested) Pension scheme and special allowances to pensioners
Earnings-related social security pensions:
One general social insurance scheme covering all employees and self-employed
persons, providing old-age, disability and survivors’ pensions;
Government Employees Pension Scheme (paid from the Government budget) and
other public sector (local gov.) employees pension schemes
Voluntary Provident Funds (providing
defined-contribution lump-sum benefits),
covering about 103.000 employees.
LV
Minimum guarantee pensions:
Through the state social security benefit, if the person’s insurance record <10years.
Earnings-related social security pensions:
The minimum of the earnings-related pension system is paid with a length-of-service
supplement to the amount of the state social security benefit, if the contribution record
exceeds 10 years.
One social insurance old-age pension scheme, which is a defined-benefit scheme for
those, retired before 1996 and a notional defined contribution scheme for those retired
as of 1996, providing old-age pensions. Also survivors’ pensions are based on NDC
contributions (except for those retired before 1996).
Separate provisions for disability pensions, though under the general social security
system
Specific public sector service pensions (selected professions) paid from the state
budget.
Do not exist
Statutory private schemes for the switched
part of the social security pension scheme
(mandatory for persons under the age of 30
on 1st July 2001, voluntary to persons aged
30-49. The contribution rate to be raised
from 2 to 10% of wages between 2006 and
2010.
Voluntary private schemes
LT
Minimum guarantee pensions:
Through a social assistance pension (also to young disabled persons and orphans)
Earnings-related social security pensions:
One social insurance pension scheme covering all employees and the self-employed,
providing old-age, disability and survivors’ pensions, and early retirement pensions as
of 2004,
Special state (old-age, disability and survivors’) pensions paid from the state budget to
specific groups (meritorious persons, scientists, judges, casualties, officers and
servicemen)
Do not exist
Voluntary switch of a part of the Social
Insurance pension to a private fund (started
in 2004 with a contribution rate of 2.5% of
wages, which will increase to 5.5% by 2007)
58
Voluntary private pension scheme; 0.1% of
total pension expenditure
LU
Minimum guarantee pensions:
Through means-tested minimum income provision (RMG)
Earnings-related social security pensions:
A general social insurance pension scheme for private sector workers, providing oldage, disability and survivors’ pensions
A special pension scheme for public sector employees ( 10% of pensioners)
Exists for some sectors such as banking and
for large foreign companies
HU
Minimum guarantee pensions:
Through means-tested social assistance;
Earnings-related social security pensions:
One social security pension scheme covering all employees and the self-employed,
providing old-age, early retirement, disability and survivors’ pensions.
Do not exist
MT
Minimum guarantee pensions:
Means-tested minimum pensions through social assistance (non-contributory) scheme
to persons not qualified for the contributory scheme
Earnings-related social security pensions:
One social security (contributory) pension scheme covering all employees and the
self-employed, providing old-age, disability and survivors’ pensions (apart from
unemployment, sickness and work injury benefits)
Exists only to a minor extent
NL
Minimum guarantee pensions: social assistance to those not qualifying (not lived
in NL for 50 years) to contributory flat-rate scheme
Contributory social insurance pensions:
General flat-rate old-age pensions (AOW) to all citizens;
Separate disability benefits (WAO) and survivors’ pensions (ANW); flat-rate or
earnings-related benefits.
A high number of funds (industry-wide,
company-specific and professional group
specific) for the provision of occupational oldage pensions and early retirement schemes
(VUT), covering over 90% of employees
Exists to some degree
AT
Minimum guarantee pensions:
Means-tested minimum pensions through social assistance scheme
Earnings-related social security pensions:
Harmonised social security pension schemes covering all employees and the selfemployed (gradually harmonised as of 2005), providing old-age, disability and
survivors’ pensions
.
The 2002 reform increased occupational
pension provision through the obligation to
transform the earlier severance pay into a
supplementary occupational scheme (with a
contribution rate of 1.53% of wages).
Exists only to a minor extent but the
introduction of tax-favoured private scheme
(Zukunftsvorsorge) will increase their
importance
59
Statutory private schemes for the switched
part of the social security pension scheme
(mandatory for new entrants to the labour
market as of 1998, voluntary to workers
already in the labour market). The
contribution rate is 8% of wages. The
scheme covers 60% of all workers.
Voluntary private pension schemes cover
30% of all workers.
Exists only to a minor extent
Minimum guarantee pensions:
Means-tested minimum pensions financed from the state budget, topping-up benefits
paid out from mandatory pension schemes.
Earnings-related social security pensions:
One social insurance pension scheme (ZUS), covering all employees and the selfemployed (except farmers), which is a defined-benefit scheme to those born before
1949 and a notional defined contribution scheme to those born after 1948, providing
old-age pensions.
Separate schemes for disability and survivors’ pensions under the social sec. system.
A separate scheme for farmers (KRUS), providing old-age, disability and survivors’
pensions.
Specific public sector service pensions (armed forces, police, judges etc.) paid from
the state budget.
Pre-retirement benefits paid out from the state budget.
Exists only to a very minor extent, with a very
low coverage (2% of employees).
PT
Minimum guarantee pensions:
Means-tested minimum pensions through social assistance scheme
Earnings-related social security pensions:
A general social security pension scheme covering all employees and the selfemployed in the private sector, providing old-age, disability and survivors’ pensions
(apart from short-term benefits).
A separate pension scheme (CGA) for public sector employees (incl. police and
military forces), benefits paid from the state budget.
Exists mainly for banking, insurance and
telecommunication sectors as a substitute for
the general social security scheme.
Exists only to a very minor extent
SI
Minimum guarantee pensions:
National, means-tested pensions
Earnings-related social security pensions:
One social security pension scheme covering all employees and the self-employed,
providing old-age, disability and survivors’ pensions
Flat-rate pensions to farmers, military personnel of the Yugoslav army and for retirees
from other republics of the former SFRY
Minimum guarantee pensions:
No special minimum pension scheme, minimum subsistence for old people and
widows provided through means-tested social assistance paid out from the state budget
Earnings-related social security pensions:
One social security pension scheme covering all employees and the self-employed,
providing old-age, disability and survivors’ pensions.
Minimum guarantee pensions:
National pension scheme provides means-tested (against other pensions) minimum
pensions to all citizens, a full national pension after 40 years of living in FI. Also
means-tested housing allowances for pensioners.
Earnings-related social security pensions:
Several but harmonised social security pension schemes for different sectors of
employees and the self-employed, covering all gainfully employed, providing oldage, early retirement, disability and survivors’ pensions
Mandatory supplementary insurance for some
high-risk professions (about 26000 workers,
minor importance), voluntary collective
supplementary pensions (covering half the
employees)
voluntary individual supplementary
pensions (of minor importance in 2003)
Do not exist
Statutory private schemes for the switched
part of the social security pension scheme as
of 2005 (mandatory for new entrants and
voluntary for current employees).
Contribution rate is 9% of wages.
Supplementary occupational pensions,
accounting for about 2 % of total pension
benefits
Voluntary individual private pension
insurance, accounting for about 1% of total
pension benefits but the insured people
account for about 15% of working-age
population
PL
SK
FI
Statutory private schemes for the switched
part of the social security pension scheme as
of 1999 (mandatory for new entrants;
voluntary switch already closed).
Contribution rate is 7.3% of wages.
60
SE
UK
Minimum guarantee pensions:
National pension scheme provides means-tested (against other pensions) minimum
pensions to all citizens, a full national pension after 40 years of living in SE. Also
means-tested housing allowances for pensioners.
Earnings-related social security pensions:
One general social security (NDC) pension scheme covering all employees and the
self-employed, providing old-age pensions. The old earnings-related ATP schemes for
local and central government employees work in parallel during the phasing-out
period.
Separate disability and survivors’ pension schemes. The former formally counted as
health insurance. The widow’s pension (part of survivors’ pensions) is being phased
out.
Minimum guaranteed and contributory social insurance pensions:
Flat-rate (contributory) state basic (old-age) pensions to all citizens and means-tested
supplements through pension credits and Council taxes (financed out of taxes)
Earnings-related social security and other public pensions:
State second pension scheme, of which people can opt out of occupational pensions
Public service pensions paid from the state budget.
Separate disability and widows’ allowance schemes.
61
Supplementary occupational old-age pensions
for all sectors, covering 80-90% of employees.
Statutory private schemes (premium
pension) for the funded part of the social
security pension scheme; contribution rate is
2% of wages. (Note: reported as social
security pension until 2007)
A high number of funds for the provision of
occupational pensions (about 60% of
employees are contributing either to
occupational or personal pension schemes).
Personal pension provisions with tax
subsidies for persons without access to
occupational schemes were introduced in
1998;
Stakeholder pension provision with tax
subsidies without access to company
(occupational) pension schemes was
introduced in 2001.
3.2.2.
Coverage of the pension expenditure projections
These projections cover social security and other public pensions as well as mandatory private
pensions. Projections have been made both for gross and net pensions. As far as the
projections of occupational pensions are concerned, some Member States where these
pensions are of major importance have provided also these projections.
Social security and other public pensions are broken down into two categories:
• old-age and early retirement pensions (including minimum and earnings-related pensions),
with a preference to include also disability and widow’s pensions paid out to persons over
the standard retirement age;
• other pensions (disability, survivors’, partial pensions without any lower age limit,
including minimum and earnings-related pensions).
Occupational and mandatory private pensions are not broken down into sub-groups.
In general, in the 2005 projections, the coverage of public pension schemes is very good.
They include social security schemes, which are statutory and involve a contribution to the
scheme, and other public pensions which do not constitute a scheme but are paid out directly
as government expenditure (such as government sector employees or armed forces’ pensions)
or which are equivalent benefits to pensions such as minimum guaranteed benefits from
general social assistance scheme. For a couple of countries, the coverage has been improved
compared with the 2001 projection exercise by including also public sector employees’
pensions in the projections (Luxembourg and the United Kingdom) as well as disability
pensions or benefits (in Sweden). In the case of Denmark, the coverage has been made
consistent with the new definition of the general government sector by moving supplementary
occupational pensions (ATP) from public pensions into occupational pensions. Greece was
not able to provide projections covering all pension funds; partial results for the main fund
have not been included in this report.
Regarding private mandatory pensions, their inclusion in the projections is of great
importance as it concerns pension provision that has been switched from social security
schemes to private funds. In all of the new Member States, where these private mandatory
schemes exist, they are recorded under the private sector pensions. Such a scheme also exists
in the Swedish pension system. However, this scheme will be included in the general
government sector in the national accounts up to 2007. Accordingly, the Swedish private
mandatory scheme is included in the public sector schemes in these projections (additional
information on its importance is provided in Table 3-16). All voluntary private schemes
(except the part in Lithuania that can be voluntarily switched from the social security scheme
into a private scheme) are excluded from these projections.
Regarding the coverage of occupational pension schemes, only the Netherlands and Sweden
provided a full coverage of occupational pensions. However, occupational pensions form a
significant proportion of total pensions also in Denmark, Ireland and the United Kingdom and
can be considered being equivalent to earnings-related social security pensions in most
Member States. Their absence in these projections is a major caveat in the coverage of total
pensions. For Denmark, occupational pensions currently amount to over 3 per cent of GDP. In
the United Kingdom, spending on funded defined benefit private pensions and private money
purchase schemes (occupational and personal) in 2005 is estimated to have been around 4
percent of GDP38. Furthermore, a growing number of Member States are increasing the
provision of complementary occupational pensions, for instance Belgium, Germany, Spain,
Italy, Austria and Poland. Currently, their importance is at most in the order of 1-2 per cent of
GDP. All countries (except Slovenia and Sweden) have excluded such complementary
occupational pensions in the projections.
Table 3-2 Coverage of pension schemes in the 2004 projections
BE
CZ
DK
Schemes covered in the projections and their
desegregation 1)
Schemes not covered
Social security pensions: old age and early pensions
Minimum benefits w63/m65+
E-r old-age 60+ and widows, public sector
E-r old-age 60+ and widows, private sector
E-r old-age 60+ and widows, self-employed
Early pensions (pre-pensions) 58+, private sector
Early retirement pensions (pre-pension) for labour market
reasons 50-57, private sector
Social security pensions: other
Disability pensions -64, private sector
Disability pensions -64, self-employed
Social security pensions: old age and early pensions
Minimum and e-r old-age pensions, 61+ (63+ as of
2013), all sectors
Proportional old-age pensions, 65+, all sectors
Widows and disability pensions, 55+
Early pensions (with temporary or permanent reductions)
Social security pensions: other
Widows and disability pensions -54
Orphans pensions
Social security pensions: old age and early pensions
Public flat-rate old-age pensions and means-tested
supplements, all citizens 65+
Civil servants old-age pensions 65+, central and
local government
Voluntary early retirement schemes, all wage earners
Social security pensions: other
Disability and survivors’ pensions, -64
Pre-pensions include only the part paid from
unemployment benefit scheme, not the
complement paid by the employer.
Occupational pension schemes (pensions 1.3%
of GDP in 2004)
Occupational pensions
Labour market pensions (e-r old-age, disability
and spouse’s pensions), private sector (ATP)
Labour market pensions (e-r old-age, disability
and spouse’s pensions), new public sector
schemes (ATP)
Labour market supplementary pensions (SP)
Special pension savings plan (SAP)
Labour market supplementary pensions for
recipients of anticipatory pension
Social security
Minimum benefits to elderly (social
assistance); 0.3% of GDP
Farmers and miners pensions (0.8% of GDP)
Occupational pensions, of growing importance
(1.3% of GDP in 2004). 30% of newly retired
persons receive also occupational pensions and
60% of employees contribute to such schemes.
Individual funded pensions, schemes at an early
DE
Social security pensions: old age and early pensions
E-r old-age, widows and disability schemes, all ages,
General scheme and life-time civil servants
Early pensions for long-time workers
Early pensions for labour market reasons
Early pensions for women
Early pensions for severely handicapped
Social security pensions: other
(covered above; not shown separately)
38
UK: This estimate is from the second report of the UK Pensions Commission (A New Pension
Settlement for the Twenty-First Century, November 2005), which also includes projections of future
private pension spending. The projections are not produced on the same basis (in terms of the
underlying assumptions and the modelling and projection methodologies used) as the UK projections of
state and public service pensions included in public pensions in this report and are therefore not directly
comparable. Further details can be found at
http://www.pensionscommission.org.uk/publications/2005/annrep/annrep-index.asp.
63
building stage, only contributions to the schemes.
EE
GR
ES
Social security pensions: old age and early pensions
Minimum flat-rate pensions, all citizens
E-r old-age pensions; length-of-service component to 59.5+w
and 63+m in 2005, 63+ for both sexes as of 2016, all sectors
(Pension Ins. Fund)
Early pensions (possible to retire 3 years before the statutory
retirement age), all sectors
Social security pensions: other
Disability and widows’ pensions, all ages, all sectors (Pension
Insurance Fund)
Private mandatory pensions
Individual funded pensions, mandatory for young
persons born 1983
Social security pensions: old age and early pensions (planned
coverage, projections not yet completed)
Minimum pensions (State budget and EKAS (Pensioners
Social solidarity Fund)
Old-age flat-rate? pensions, farmers aged? (OGA)
Old-age pensions, other self-employed (TEVE)
E-r old-age and supplementary old-age pensions,
private sector (IKA and merged funds)
E-r old-age pensions, public sector (civil servants,
army, public power corporation), aged?
E-r supplementary pensions, public sector (auxiliary funds)
Disability pensions, all ages?
Widows pensions, all ages?
Early pensions, aged ?
Social security pensions: other
Orphans pensions
Social security pensions: old age and early pensions
E-r old-age and early retirement pensions for private sector
employees, the self-employed, regional and local government
Flat-rate old-age and early retirement pensions for central
government employees.
Social security pensions: other
Disability and survivors’ pensions for private sector
employees, self-employed, regional, local and central
government
War pensions
FR
Social security pensions: old age and early pensions
Minimum old-age and widows’ pensions (State budget)
E-r old-age pensions, 60+, private sector (CNAVTS,
national pension fund for salaried workers)
E-r old-age pensions, 60+, agricultural workers (MSA,
mutual agricultural solidarity fund)
Mandatory supplementary funded old-age pensions,
all workers in the private sector (ARRCO, association
of suppl. pension schemes for non-executive employees)
Mandatory supplementary funded old-age pensions,
executive workers, private sector (AGIRC, general
association of pension institutions for executives)
E-r old-age pensions, 57.5+ (60+ as of 2008), public
sector (Civil and military pension code, CNRACL, local
government and hospitals), specific funds for public sector
enterprise workers)
E-r old-age pensions, self-employed (CANCAVA
(craftsmen), ORGANIC (tradesmen), CNBF (lawyers),
CNAVPL (independent professions))
Disability and widows pensions, 60+, all sectors (FSV)
Anticipated old-age and early retirement pension (UNEDIC)
Small anticipatory pension schemes
The new disability scheme (within health
insurance), established in 2004.
64
IE
IT
CY
LV
LT
Social security pensions: old age and early pensions
Minimum flat-rate old-age non-contributory pensions, 66+
(dependant adults only), all sectors 39
Widow(er)s non-contributory pensions, 66+ , all sectors 3
Blind persons, carers and lone parents, 66+, all sectors 3
Flat-rate contributory and retirement pensions, 65+
(dependant adults only), private sector, self-employed and some
civil servants 40
Invalidity pensions, 65+, private sector, self-employed,
Widow(er)s contributory pensions, 66+, all sectors 3
Social security pensions: others
Widow(er)s non-contributory and non-contributory pensions,
-65, all sectors 3
Blind persons, carers, -65, all sectors 3
Disability pensions, -66, and invalidity pensions -64, private
sector, self-employed, some civil servants 4
Pre-retirement allowance, 55-64, all sectors 3
Public sector (occupational) pensions (Civil service, defence,
Gardai, education, health and local authorities, noncommercial state bodies)
Social security pensions: old age and early pensions
Social assistance pensions (State budget)
E-r old-age, disability and widows pensions,
w60+/m65+, all sectors (AGO, general social insur. scheme)
Early retirement, disability and widows pensions,
w55-59/m55-64, all sectors (AGO)
Early (seniority) pensions, all sectors (AGO)
Social security pensions: other
Disability and widows pensions, -54, all sectors
Social security pensions: old age and early pensions
General Social Insurance scheme covering e-r old-age and
widows’ pensions
Early old-age pensions, 58-64,
Invalidity and disablement pensions, -62
Government Employees Pension scheme covering old-age,
widows’ and disability pensions
Occupational pensions:
Private sector schemes
Occupational pensions; of minor importance
Social security pensions: old age and early
pensions
Social (minimum) pension scheme and special
allowances to pensioners
Occupational pensions:
Voluntary provident Funds
Social security pensions: old age and early pensions
State (social security) benefits (those with less
than 10 years insurance records), 67+ , (State budget)
Old-age minimum guaranteed pension, 62+
E-r old-age DB pensions, granted -1995, all sectors
E-r old-age NDC pensions, 62+, granted 1996+, all sectors
Special service pensions (early pensions), selected
professions, public sector
Disability pensions, granted -1995 and not transformed to
old-age pensions, all sectors
Survivors’ pensions (for widows during the transition period)
Social security pensions: other
Disability pensions, -62, all sectors
Survivors’ pensions -24,
Special service survivors pensions, public sector
Private mandatory pensions
Individual funded old-age pension, mandatory for
persons born 1971+
Social security pensions: old age and early pensions
Social assistance pensions, w60+/m62.5+ ; (State budget)
Old-age, disability and widows pensions,
39
IE: while all sectors of the economy are eligible to apply for these pensions, some sectors may not be eligible to receive
them given the means-tested nature of the schemes.
40
IE: Civil and Public Servants recruited after 6 April 1995 are in the full Pay Related Social Insurance class and will
therefore receive an integrated Social Security contributory and occupational pension upon retirement. Those recruited
before 6 April 1995 pay a lower rate of Pay Related Social Insurance and are not entitled to all benefits.
65
LU
HU
MT
NL
AT
PL
w60+/m62.5+, all sectors (Soc insurance scheme)
Officials and military personnel disability and widows
pensions, w60+/m62.5+, public sector (State budget)
Special public service (state) pensions, selected
professions (State budget)
Social security pensions: other
Social assistance pensions, -w59/-m62.4
Disability and widows pensions, -w59/-m62.4, all
sectors (Soc. Insurance scheme)
Officials and military personnel disability and widows
pensions, -w59/-m62.4, public sector (State budget)
Length of service pensions, selected professions,
public sector (Soc. sec. scheme)
Early retirement unemployment benefit (Unemployment
fund), changed into early retirement pension as of mid 2004
(Social insurance scheme as of mid 2004)
Private mandatory pensions
Individual funded old-age pension, voluntary, all sectors
Social security pensions: old age and early pensions
E-r old-age, early retirement and disability pensions, 65+,
private sector & self-employed (RGAP (general pension
insurance scheme)
E-r old-age, early retirement and disability pensions, 65+ ,
public sector (RSP, special pension scheme), state budget
Social security pensions: other
Disability (-64 years) and survivors’ pensions, all sectors
Social security pensions: old age and early pensions
Social allowances equivalent to pensions to persons 62+
E-r old-age and anticipatory old-age pensions, all sectors
Survivors pensions, 62+, all sectors
Disability pensions, 62+, all sectors
Social security pensions: other
Disability pensions, -61, all sectors
Survivors pensions, -61, all sectors
Pension-like regular social allowances, -61
Private mandatory pensions
Individual funded pensions, mandatory to persons
entering the labour market
Social security pensions: old age and early pensions
National minimum pensions and increased national minimum
pensions
E-r old-age (two-thirds) pensions, w60+/m61+; s-e 65+
Social security pensions: other
Pensions other than those listed above, notably disability and
survivors’ pensions and some pensions, which will be phased
out over a transition period, to specific groups of pensioners
Social security pensions: old age and early pensions
Public flat-rate old-age pensions, 65+, all citizens (AOW)
Widows pensions, w55+, all sectors (ANW)
Social security pensions: other
Disability benefits, all sectors (WAO)
Occupational pensions
Occupational old-age pensions, 65+, all sectors
Occupational early retirement pensions, all sectors (VUT)
Social security pensions: old age and early pensions
E-r old-age, disability and early retirement pensions,
w60+/m65+, private sector (ASVG, gen. soc. ins. Scheme)
E-r old-age, disability and early retirement pensions,
w60+/m65+, public sector
E-r old-age, disability and early retirement pensions,
w60+/m65+, farmers and self-amployed
Social security pensions: other
Survivors’ pensions, all ages, all sectors
Social security pensions: old age and early pensions
E-r DB old-age, w60+/m65+, disability, widows and
early retirement pensions, w55-59/m55-64, to persons
born -1948 and to those people who earned fully their
Minimum benefits (RMG, social assistance)
Handicap support, political compensation
allowances
Social security pensions: old age and early
pensions:
Minimum pensions (Ausgleichszulagen),
financed by taxes
Social security pensions: old age and early
pensions:
Minimum means-tested pensions
66
PT
SI
SK
FI
pension rights before the end of 2006, private
and public sector, self-employed (ZUS, Social ins. institute)
E-r NDC old-age and anticipatory pensions, to persons born
1949- (with the exception of the transitional group), private
and public sector, self-employed (ZUS, Social insurance
fund)
E-r DB old-age, disability and widows pensions, all
ages, farmers (KRUS, Farmers social ins. scheme)
Armed forces old-age pensions (State budget)
Social security pensions: other
Disability and widows pensions, -54, private and
public sector, self-employed (ZUS)
Private mandatory pensions
Individual funded old-age pensions, mandatory to
persons born 1969+ and voluntary to those born 1949-68
joining the scheme by the end of 1999
Social security pensions: old age and early pensions
Social pensions (minimum, means-tested and nonContributory, State budget): old-age, 65+, disability
pensions, 65+
General Contributory (social insurance) scheme: e-r old-age
55+; disability pensions, 65+; employees and self-employed
of the private sector
RESSAA, (Spec. soc. sec. scheme for agriculture workers),
e-r old-age, 65+, disability pensions, 65+
CGA (Civil servants’ pension scheme), e-r old-age, 55+,
disability pensions, all ages
Social security pensions: other
Social pensions (means-tested non-contributory), disability
pensions, -64, widows and orphans pensions, all ages
General contributory scheme & RESSAA, disability pensions,
-64, widows and orphans pensions, all ages
Civil servants scheme, widows and orphans pensions, all ages
Social security pensions: old age and early pensions
National (state) minimum pensions (State budget)
E-r old-age (w58-63+/m58-65+),
Disability and widows pensions, all ages, all sectors
Special compulsory pensions to workers in high-risk
occupations, private and public sector
Flat-rate pensions for farmers, the military personnel of the
Yugoslav army and retirees from other republics of former
SFRY
Occupational pensions :
Collective supplementary pensions
Social security pensions: old age and early pensions
Social pensions, 65+, all sectors (State budget)
E-r old-age, w53-57+/m60+ (w62+ 2016 and m62+
2006), disability and widows pensions, w55-56/
m55-64, all sectors (Social insurance scheme)
Social security pensions: other
Disability and widows pensions, -54, orphans
pensions
Private mandatory pensions
Individual funded old-age pension, mandatory to
persons entering labour market 2005+
Occupational pensions (of minor importance)
Occupational pensions:
Supplementary schemes for some sectors
(banking and insurance)
Social security pensions: old age and early pensions
National (minimum) pension (Nat. pension insurance), 65+ ;
E-r old-age, 63+, early pensions, private sector and the selfemployed: (TEL, private sector employees, most industries),
(LEL, private sector industries with short-time contracts),
(YEL, self-employed), (MYEL,farmers), (TaEL , artists); and
the public sector: (VEL (central government employees),
KVTEL (municipal sector employees), KiEL (church empl.),
unemployment pensions, 60-62,
Social security pensions: other
National (minimum) disability and survivors’ pensions, -64;
67
E-r disability and survivors pensions, -62, all sectors (early
pensions changed into old- age pensions at the age of 63 and,
then, included in the above category)
Occupational pensions:
Collective mandatory and voluntary supplementary schemes
SE
UK
1)
Social security pensions: old age and early pensions
Minimum pensions (State budget)
E-r NDC old-age and anticipated pensions, flexible age, all
sectors (Social insurance scheme)
Individual mandatory funded old-age pensions, premium
pensions, (Note: reported as part of social security scheme
for the whole projection period but should be included in the
private insurance sector as of 2007)
Social security pensions: other
Disability pensions, 19-64, and survivors benefits, all ages
Occupational pensions
Occupational (supplementary) pensions, private and public
sector employees (old and new schemes)
Social security (and other public) pensions: old age and early
pensions
Basic state (minimum) pensions + their additions (winter fuel
allowance), 66+, all citizens (National insurance scheme)
Pension credits and Council tax benefits, 60+, all
citizens (State budget)
State second pension (S2P)/ State earnings-related
pensions (SERPS), w60+/m65+ (w65+ 2020), all
sectors (National insurance scheme)
Widows benefits + their additions, 55+, all sectors
E-r old-age pensions, 60+, public sector employees (State
budget)
Social security pensions: other
Widows benefits, -54, all sectors
Public pensions
Disability benefits
Occupational pensions
Supplementary funded old-age pensions, private
sector; important part of the pension system
E-r = earnings-related
Pension contributions and asset accumulation in pension funds have been included in these
projections on a voluntary basis. Most Member States were able to provide these projections.
However, some Member States (Belgium, Spain) indicated that they had difficulties
projecting contributions as the pension contribution is not defined separately but is included
in the overall social security contribution covering all social security benefits. Portugal and
Malta have provided projections for the total social security contribution (including also the
part of the contribution which is used for benefits other than pensions). Further, it should be
noted that, in Denmark, social security pensions are financed by general taxes and virtually no
contributions (except a minor contribution to voluntary early retirement schemes) are paid by
the employers or employees.
The projections on assets in pension funds (with the exception concerning the coverage of
occupational pensions) have been provided by all countries where these assets are important.
3.2.3.
The concepts of pensions, contributions and assets
The following concepts have been used in the projection exercise:
Pensions cover pensions and equivalent cash benefits granted for a long period (over one
year) for old-age, early retirement, disability, survivors (widows and orphans) and other
specific purposes which should be considered as equivalents or substitutes for the above68
mentioned types of pensions, including pensions due to reduced capacity to work or due to
labour market reasons. Pensions and benefits can be paid out from specific schemes or
directly from government budgets. Pensions should not include (additional) benefits in the
form of reimbursements of certain costs to the beneficiaries or directly provided goods and
services for the specific needs of the beneficiaries, including transfers from pension
institutions to other social security schemes such as health schemes. The administrative costs
of pension schemes should not be included.
Gross pensions cover pensions recorded as gross benefits, i.e. without a deduction of tax and
compulsory social security contributions by beneficiaries paid on benefits. In those countries
where pensions are not taxable income the gross pensions are equal to net pensions.
Net pensions cover pensions recorded as net benefits, i.e. deducting from the gross pension
the estimated tax and compulsory social security contributions by beneficiaries paid on
pensions. Member States were advised to use relatively straightforward approximations for
taxes and social security contributions paid by the pensioners. The aim of presenting net
pensions as a share of GDP is to give a picture of the order of magnitude which taxation plays
in the magnitude of pension expenditure. Regarding the evolution of the taxation over the
projection period, it is assumed that the taxation in real terms remains at the level of 2004 unless there are changes in the taxation regime of pensions - and, thus, the 2004 rules can be
applied over the whole projection period.
Social security and other public pensions (later in the report also called ‘public pensions’)
cover, first, social security schemes that are statutory and that the general government sector
administers. The pensions provided by the social security schemes can be either earningsrelated, flat-rate or means-tested. In addition, this category covers also pensions that are paid
directly from the state or other public sector entity budgets without forming a specific scheme
such as special pensions to public sector and armed force’s employees. Also cash benefits that
are equivalent to pensions, notably social assistance, are included. The aim is to cover those
pension schemes that affect the public finances, in other words, the schemes that are
considered to belong to the general government sector in the national accounts system.
Occupational pensions are pensions provided by schemes that link the access of an individual
to such a scheme to an employment relationship between him/her and the scheme provider
and that are based on contractual agreements between employers and employees either at the
company level or their organisations at the union level rather than being statutory by law. The
schemes are run by private sector pension funds, insurance companies or the sponsoring
companies themselves (the latter may appear only in balance sheets).
Private mandatory pensions are private individual pensions that are statutory and based on
individual insurance contracts between the individual and the private pension scheme
provider, usually an insurance company or a pension fund. In particular, the pension
expenditure projections cover the individual schemes that switch a part either voluntarily or
statutorily (especially to new entrants to the labour market) of the current social security
scheme to private funds. Such schemes will have an increasing relevance in the future in a
number of countries (SE, EE, HU, LV, LT, PL and SK).
Old-age and early pensions are considered as one category of pensions due to the fact that in
many countries a proper distinction between these pensions cannot be made, either because
early retirement is built-in into the old-age pension system, or because the standard retirement
age varies between sexes and will increase or become more flexible with time. Early pensions
69
include, in addition to genuine (actuarial) early retirement schemes, other early pensions that
are granted for a specified age group below the statutory retirement age primarily on the basis
of reduced work capacity or due to labour market reasons. In addition, disability and widow’s
pensions paid out to persons over the standard retirement age are included in this category in
order to properly reflect the expenditure related to old-age. Pensions in this category include
both earnings-related pensions and flat-rate or means-tested minimum pensions.
Other pensions include disability, survivors’ and partial pensions paid to persons below the
standard retirement age and without any lower age limit. These include both earnings-related
pensions and flat-rate or means-tested minimum pensions of these types.
Contributions include contributions to pension schemes paid both by employers and
employees as well as self-employed persons. The projection of the contributions is based on
the unchanged contribution rate of 2004, unless there are clear policies that the contribution
rate changes over time. The purpose is to provide information as to whether a financial gap in
the pension system exists. If the pension contribution is part of a broader social security
contribution rate, an estimate should be provided for the share of the pension contribution,
e.g. on the basis of the most recent expenditure structure. If the pension is financed by general
tax revenues, no estimate should be provided here. If the state is defined as a third contributor
to the pension scheme (Luxembourg and Malta, in both countries paying an equal share (1/3)
of the total contribution along with the employer and the employee), also the state
contribution can be included in the contributions.
Assets of pension funds take into account both the increases in the revenues of the pension
funds and the withdrawals for the payment of pensions. For the rate of return on assets,
defined as the average of the assets at the beginning and the end of the year, the assumption of
the fixed annual real return of 3.0% is used. This rate is assumed to cover also the
administrative expenses of the fund and no calculations have been made on the accumulation
of the funds, net of administrative expenses. The information on the total value of assets in
pension funds, including pre-financing to specific reserves within the government sector, is
provided separately concerning social security schemes, occupational pension schemes and
private pension schemes.
Inclusion of the impact of pension reforms: The (future) impact of pension reforms enacted
by the end of 2004 (in the case of Portugal, also the impact of the Spring 2005 reform) is
included in the projections.
3.3.
Baseline projection results
3.3.1.
Projected trend in public pension expenditure and a comparison with the
2001 projection
Gross social security and other public pensions correspond conceptually to the coverage of
the 2001 projections of public pension expenditure. Table 3-3 presents the projections for
public pension spending before taxes and social security contributions paid out to the
beneficiaries, as a percentage of GDP. Concerning the coverage of public pension schemes in
these projections, it can be considered as being very good for all countries, including all
significant schemes.
70
Table 3-3 Gross public pension expenditure as a share of GDP between 2004 and 2050
Public pensions, gross as % of GDP
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
15,7
15,5
4,3
0,8
5,1
12,2
14,0
1,1
4,5
5,6
13,5
12,8
3,3
0,0
3,3
12,3
12,8
13,1
0,9
0,8
1,7
4,7
4,4
4,2
-1,9
-0,5
-2,5
Country
2004
2010
2015
2020
2025
2030
BE
10,4
10,4
11,0
12,1
13,4
14,7
CZ
8,5
8,2
8,2
8,4
8,9
9,6
DK
9,5
10,1
10,8
11,3
12,0
12,8
DE
11,4
10,5
10,5
11,0
11,6
EE
6,7
6,8
6,0
5,4
5,1
2040
GR
ES
8,6
8,9
8,8
9,3
10,4
11,8
15,2
15,7
3,3
3,9
7,1
FR
12,8
12,9
13,2
13,7
14,0
14,3
15,0
14,8
1,5
0,5
2,0
IE
4,7
5,2
5,9
6,5
7,2
7,9
9,3
11,1
3,1
3,2
6,4
IT
14,2
14,0
13,8
14,0
14,4
15,0
15,9
14,7
0,8
-0,4
0,4
CY
6,9
8,0
8,8
9,9
10,8
12,2
15,0
19,8
5,3
7,6
12,9
LV
6,8
4,9
4,6
4,9
5,3
5,6
5,9
5,6
-1,2
-0,1
-1,2
LT
6,7
6,6
6,6
7,0
7,6
7,9
8,2
8,6
1,2
0,7
1,8
LU
10,0
9,8
10,9
11,9
13,7
15,0
17,0
17,4
5,0
2,4
7,4
HU
10,4
11,1
11,6
12,5
13,0
13,5
16,0
17,1
3,1
3,7
6,7
MT
7,4
8,8
9,8
10,2
10,0
9,1
7,9
7,0
1,7
-2,1
-0,4
NL
7,7
7,6
8,3
9,0
9,7
10,7
11,7
11,2
2,9
0,6
3,5
AT
13,4
12,8
12,7
12,8
13,5
14,0
13,4
12,2
0,6
-1,7
-1,2
PL
13,9
11,3
9,8
9,7
9,5
9,2
8,6
8,0
-4,7
-1,2
-5,9
PT
11,1
11,9
12,6
14,1
15,0
16,0
18,8
20,8
4,9
4,8
9,7
SI
11,0
11,1
11,6
12,3
13,3
14,4
16,8
18,3
3,4
3,9
7,3
SK
7,2
6,7
6,6
7,0
7,3
7,7
8,2
9,0
0,5
1,3
1,8
FI
10,7
11,2
12,0
12,9
13,5
14,0
13,8
13,7
3,3
-0,3
3,1
SE
10,6
10,1
10,3
10,4
10,7
11,1
11,6
11,2
0,4
0,2
0,6
UK
EU15 1)
6,6
6,6
6,7
6,9
7,3
7,9
8,4
8,6
1,3
0,7
2,0
10,6
10,4
10,5
10,8
11,4
12,1
12,9
12,9
1,5
0,8
2,3
EU10
EU12 1)
10,9
9,8
9,2
9,5
9,7
9,8
10,6
11,1
-1,0
1,3
0,3
11,5
11,3
11,4
11,8
12,5
13,2
14,2
14,1
1,6
0,9
2,6
1)
10,6
10,3
10,4
10,7
11,3
11,9
12,8
12,8
1,3
0,8
2,2
EU25
1) excluding Greece
As regards the starting position in 2004, public pension spending accounted for an average of
about 10.6% of GDP in the EU Member States, with a large variation from 4.7% of GDP in
Ireland to 14.2% of GDP in Italy. The low levels of public spending on pensions in Ireland
and the United Kingdom stem from the fact that the public pension schemes primarily provide
flat-rate pensions, while occupational pensions play an important role in the total provision of
pensions. Public pension spending is clearly below the EU average also in a number of EU10
Member States such as Cyprus and Malta as well as Estonia, Latvia, Lithuania, and Slovakia.
In the latter group of countries, this can be attributed partially to the fact that the current
pensions are relatively flat-rate as most of pensioners acquired their pension rights before the
collapse of the communist regime in societies which had relatively small wage differences,
and in some cases to the fact that the levels of pensions have been based only on the length of
service. It is also partially due to the fact that, in recent years, economic growth rate has been
rapid thereby reducing spending as a percentage of GDP from the figures seen, for example,
in 2000.
In contrast, high GDP percentages of public spending in countries, such as France, Austria,
Poland and Italy, reflect the fact that the pension provision mainly relies on social security
schemes and that the main scheme is an earnings-related one.
The main results of the 2005 projections can be presented as follows:
•
the projections show very different increases in public pension spending over the
period between 2004 and 2050, ranging from a decrease of 5.9 percentage points of
GDP in Poland to an increase of 9.7 p.p. of GDP in Portugal and 12.9 p.p. of GDP in
Cyprus;
71
•
in the EU15 Member States, public pension spending is projected to rise by 2.3 p.p. of
GDP on average and to rise in all countries except in Austria. In Austria, the spending
peaks around 2035 but decreases thereafter. This can be attributed to the effects of the
latest reforms since 2000. These reforms have increased legal retirement age, linked
contributions more closely to benefits with actuarial reductions for early pensions and
will switch from a wage to a price indexation of pensions as of 2006;
•
in Italy and Sweden, the projected increases are very small due to the fact that the
schemes are defined-contribution and, thus, the spending on pensions is driven
primarily by the accumulation of contributions;
•
relatively moderate increases (between 1.7 and 3.5 percentage points) in public
pension expenditures are projected in a great number of the EU15 Member States such
as Germany, the United Kingdom, France, Finland, Denmark and the Netherlands.
Somewhat larger increases are projected in Belgium (5.1 p.p.) and Ireland (6.4 p.p.).
In Ireland, the increase will largely be due to the maturing of the social security
pension system;
•
the largest challenges on pension expenditure in the EU are faced by Portugal (an
increase of 9.7 p.p. of GDP), Luxembourg (7.4 p.p.) and Spain (7.1 p.p.);
•
in the EU10 Member States, public pension expenditure is projected to decrease by 1
p.p. of GDP by 2030 on average but then to rise by 1.3 p.p. by 2050, with an overall
increase by 0.3 p.p. between 2004 and 2050. However, the developments show very
diverse trends in different countries: from a decrease of 5.9 p.p. of GDP in Poland to
an increase of 6.7 p.p. in Hungary ,7.3 p.p. of GDP in Slovenia and 12.9 p.p. in
Cyprus. Excluding Poland, in the remaining 9 new Member States, the projected
increase in public pension spending is 4.9 p.p. of GDP.
•
the projected decreases in Poland, Estonia and Latvia, as well as the projected small
increases in Lithuania and Slovakia, stem partly from the pension reforms enacted
during the last decade. These countries have switched part of the public old-age
pension scheme into private funded schemes. Thus, the public provision of pensions
will decrease while the private part, which remains mandatory, will increase. Another
reason for the projected decrease in terms of the percentage of GDP is that the GDP
growth rate is projected to be relatively high, in particular during the next two
decades. This growth rate will be higher than the increase in the level of pensions, as
pensions are indexed to prices only or only partially to wages.
•
in Malta, the projected decrease in pension spending after 2020 stems from the current
parameters of the pension scheme, notably, the indexation of the maximum pension to
prices, which would lead to relatively flat-rate pensions over time.
•
the challenges faced by Cyprus, Slovenia, Hungary and the Czech Republic are among
the biggest in the whole of the EU. While Slovenia and the Czech Republic have
undertaken parametric reforms of their pension systems during the 1990s, these
systems remain predominantly pay-as-you-go public pension schemes. The large
increase in the Slovenian pension system is largely due to the fact that pensions will
be fully indexed to the net wage growth as of 2006 (in 2001-2005, 80% to wages and
20% to prices).
72
•
in Hungary, the dynamic effect of the increasing wage level on the level of new
pensions is projected to weigh more than the decrease due to the partial switch into a
private scheme. Also, recent measures include improvements in the widow’s pension
level and a gradual introduction of the 13th month pension. Furthermore, the
introduction of taxes on pensions in 2013 will result in an additional increase in gross
pensions while it should not affect net pensions. As a result, a significant overall
increase in (gross) public pension spending as a share of GDP is projected.
Table 3-4 Comparison of the 2005 projections of gross public pension expenditure as a
share of GDP with the 2001 projections
2 0 0 5 p r o je c t i o n s
2050
2 0 0 4 -5 0
C o u n try
2004
BE
1 0 ,4
1 5 ,5
5 ,1
CZ
8 ,5
1 4 ,0
5 ,6
2 0 0 1 p r o je c t i o n s
2005
2050
2 0 0 5 -5 0
9 ,5
1 3 ,3
3 ,8
DK
9 ,5
1 2 ,8
3 ,3
1 1 ,3
1 3 ,3
2 ,0
DE
1 1 ,4
1 3 ,1
1 ,7
1 1 ,4
1 6 ,9
5 ,5
EE
6 ,7
4 ,2
-2 ,5
1 2 ,2
2 4 ,8
1 2 ,4
8 ,6
1 5 ,7
7 ,1
8 ,8
8 ,5
1 2 ,8
1 4 ,8
2 ,0
4 ,7
1 1 ,1
6 ,4
1 2 ,2
4 ,5 2)
1 7 ,3
1 5 ,8 1)
IT
1 4 ,2
1 4 ,7
0 ,4
1 3 ,8
1 4 ,1
0 ,3
CY
6 ,9
1 9 ,8
1 2 ,9
LV
6 ,8
5 ,6
-1 ,2
LT
6 ,7
8 ,6
1 ,8
LU
1 0 ,0
1 7 ,4
7 ,4
7 ,4
9 ,3
1 ,9
HU
1 0 ,4
1 7 ,1
6 ,7
MT
7 ,4
7 ,0
-0 ,4
NL
7 ,7
1 1 ,2
3 ,5
8 ,3
1 3 ,6
5 ,3
AT
1 3 ,4
1 2 ,2
-1 ,2
1 4 ,5
1 7 ,0
2 ,5
PL
1 3 ,9
8 ,0
-5 ,9
PT
1 1 ,1
2 0 ,8
9 ,7
1 0 ,9
1 3 ,2
2 ,3
SI
1 1 ,0
1 8 ,3
7 ,3
5 ,0
GR
ES
1)
FR
IE
2)
9
2)
3 ,6
4 ,5
SK
7 ,2
9 ,0
1 ,8
FI
1 0 ,7
1 3 ,7
3 ,1
1 0 ,9
1 5 ,9
SE
1 0 ,6
1 1 ,2
0 ,6
9 ,2
1 0 ,7
1 ,5
UK
6 ,6
8 ,6
2 ,0
5 ,3
4 ,4
-0 ,9
E U 15
1 0 ,6
1 2 ,9
2 ,3
1 0 ,4
1 3 ,3
2 ,9
1 ) F R : 2 0 4 0 in t h e 2 0 0 1 p r o je c t io n
2 ) I E : a s % o f G N P in t h e 2 0 0 1 p r o je c t io n , c o r r e s p o n d in g a p p r . t o 3 . 8 % a n d 7 . 7 % o f G D P .
The comparison between the results of the 2005 and 2001 projections presented in Table 3-4
can be made only for the EU15 Member States because only they were included in the 2001
projection exercise. Before comparing the projected increases, changes in the starting
positions should be taken into account. It is more appropriate to compare the 2004 base year
in the current projection with the projection for 2005 in the 2001 projection than the base year
of 2001. In about half the countries (DE, ES, FR, IT, NL, PT, FI), the level of public pension
expenditure as a percentage of GDP in the starting position is broadly the same as in the 2001
projections, while in most of the remaining countries the starting level is 1-2 percentage
points higher. In many cases, this difference can be attributed to a broader coverage of
pensions such as the inclusion of public sector employees’ pensions in Luxembourg and the
United Kingdom. In Sweden, the disability pensions have been added in the 2005 projection.
73
In contrast, the Danish spending is almost 2 percentage points lower due to the exclusion of
supplementary occupational pensions (ATP) from the government sector.
The main findings of a comparison between the two projections can be concluded as follows:
• in half the EU15 Member States (DE, ES, FR, NL, AT, FI and SE), the projected
increase in public pension spending between 2005 and 2050, according to the current
projections, is smaller than in the 2001 projections. The smaller increase can be
largely attributed to major pension reforms undertaken since 2001, in particular in DE,
FR, AT and FI. Reforms undertaken in other countries have probably affected the
projected evolution of pension expenditure, but their effect is more difficult to
disentangle by comparing the results of the 2001 and 2005 projections. Table 2-6 of
the Annex provides a short description of recent reforms in Member States;
•
in Italy, the projected increase in public pension spending between 2004 and 2050 is
virtually the same, while the recent reform increasing the standard retirement age as of
2008 will decrease pension spending over the period of 2010-2040. Belgium,
Denmark, Ireland, Luxembourg, Portugal and the United Kingdom project larger
increases than in the 2001 projection. The projected larger increase in public pension
spending in the United Kingdom is mainly due to the measures that have increased the
level of social insurance pensions;
•
in Luxembourg and Portugal, the 2005 and 2001 projections differ greatly from each
other and the differences are due to several factors. In the case of Portugal, the revised
population projections are significantly more unfavourable than those in the 2001
exercise and, consequently, they result in a less favourable macroeconomic
framework. Moreover, minimum pensions have converged to minimum wages,
thereby increasing the average level of pensions. For Luxembourg, the
macroeconomic framework has been substantially revised, resulting in a less
favourable projection regarding long-term economic development. Furthermore, the
projection models have been improved.
Another explanation for changes in projected public pension expenditure is the population
projections, notable changes in life expectancy and old-age dependency ratios. Table 3-5
below provides an overview of the changes in forecasted life expectancies and Table 3-6 of
changes in the old-age dependency ratio between the 2005 and 2001 projections. The most
significant changes in demographic projections (the 2001 projections were based on the 1995
census and the 2005 projections on the 2000 census) were the following:
•
in the EU15, life expectancies at birth in the base year of the projections are, on
average, more than one year higher for men and almost one year higher for women in
the 2005 projections than in the previous one;
•
the projected increase in life expectancies at birth up to 2050 are about two years
higher in Portugal and for men in Italy, and about 1.5 years higher in Spain and
Ireland in the 2005 projections compared with the 2001 exercise;
•
in the EU15, on average, the old-age dependency ratio is 1.5 percentage points higher
both at the beginning and at the end of the projection period in the 2005 projections
74
compared with the previous projection. The increase in the old-age dependency ratio
is the same in both population projections.
•
the old-age dependency ratios have risen most in Portugal (10 p.p.), Ireland and
Greece (6 p.p.) and Denmark and Spain (5 p.p.) when compared the 2005 projections
with the 2001 ones.
75
Table 3-5 Life expectancies in the 2004 and 2001 population projections
M a le
2004
2 0 0 5 p ro je c tio n s
change 20042050
F e m a le 2 0 0 4
change 20042050
M a le
2 0 0 1 p ro je c tio n s
change 20002050
2000
F e m a le 2 0 0 0
change 20002050
BE
7 5 ,5
6 ,6
8 1 ,6
5 ,9
7 5 ,3
5 ,2
8 1 ,4
4 ,0
DK
7 5 ,2
6 ,2
7 9 ,6
5 ,6
7 5 ,2
4 ,2
7 9 ,6
3 ,5
DE
7 6 ,1
5 ,9
8 1 ,7
5 ,1
7 4 ,7
5 ,3
8 0 ,8
4 ,2
GR
7 6 ,4
4 ,6
8 1 ,4
4 ,5
7 5 ,9
5 ,1
8 1 ,0
4 ,0
ES
7 6 ,6
5 ,1
8 3 ,4
3 ,9
7 4 ,9
4 ,1
8 2 ,1
2 ,9
FR
7 6 ,2
6 ,1
8 3 ,4
4 ,5
7 4 ,8
5 ,2
8 2 ,8
4 ,2
IE
7 5 ,5
6 ,6
8 0 ,7
6 ,2
7 4 ,0
5 ,0
7 9 ,4
4 ,6
IT
7 7 ,3
5 ,5
8 3 ,2
4 ,6
7 5 ,5
5 ,5
8 2 ,0
4 ,1
LU
7 5 ,0
6 ,8
8 1 ,4
5 ,3
7 4 ,4
5 ,6
8 0 ,8
4 ,2
NL
7 6 ,2
4 ,8
8 0 ,8
4 ,3
7 5 ,5
4 ,5
8 0 ,9
4 ,1
AT
7 6 ,2
6 ,6
8 2 ,1
5 ,2
7 5 ,0
6 ,0
8 1 ,2
4 ,8
PT
7 4 ,2
6 ,9
8 1 ,0
5 ,7
7 2 ,0
6 ,0
7 9 ,2
4 ,8
FI
7 5 ,3
6 ,6
8 1 ,9
4 ,8
7 3 ,9
6 ,1
8 1 ,1
3 ,9
SE
7 8 ,1
4 ,6
8 2 ,4
4 ,3
7 7 ,3
4 ,7
8 2 ,0
4 ,0
UK
7 6 ,4
6 ,0
8 0 ,9
5 ,7
7 5 ,2
4 ,8
8 0 ,0
5 ,0
4 ,3
7 5 ,0
5 ,0
8 1 ,3
4 ,2
CY
7 6 ,3
5 ,6
8 0 ,8
CZ
7 2 ,4
7 ,4
7 8 ,8
5 ,3
EE
6 5 ,5
9 ,4
7 6 ,9
6 ,3
6 ,6
HU
6 8 ,5
9 ,6
7 6 ,8
LT
6 6 ,5
9 ,0
7 7 ,6
6 ,1
LV
6 4 ,9
9 ,3
7 6 ,2
6 ,3
MT
7 6 ,2
5 ,6
8 0 ,7
4 ,3
PL
7 0 ,5
8 ,7
7 8 ,5
5 ,9
SK
6 9 ,7
8 ,0
7 7 ,8
5 ,6
SI
7 2 ,6
7 ,3
8 0 ,2
5 ,0
E U15
7 6 ,4
5 ,8
8 2 ,2
4 ,9
E U10
7 0 ,1
8 ,6
7 8 ,2
5 ,9
E U25
7 5 ,4
6 ,3
8 1 ,5
5 ,1
Table 3-6 Dependency ratios in the 2004 and 2001 population projections
2 0 0 5 p r o je c tio n s
2 0 0 1 p r o je c tio n s
2004
2050
change
2000
2050
change
BE
2 6 ,1
4 7 ,2
21
26
45
20
DK
2 2 ,5
4 1 ,9
19
22
36
14
DE
2 6 ,8
5 1 ,7
25
24
49
25
G R
2 6 ,4
6 0 ,4
34
26
54
28
ES
2 4 ,6
6 5 ,4
41
25
60
36
FR
2 5 ,2
4 6 ,4
21
24
46
22
IE
1 6 ,4
4 5 ,2
29
17
40
23
IT
2 8 ,9
6 2 ,2
33
27
61
35
LU
2 1 ,0
3 6 ,1
15
21
38
16
NL
2 0 ,5
4 0 ,6
20
20
41
21
AT
2 2 ,8
5 2 ,4
30
23
54
31
PT
2 4 ,9
5 8 ,5
34
23
46
24
FI
2 3 ,3
4 6 ,7
23
22
44
22
SE
2 6 ,4
4 0 ,9
14
27
42
16
UK
2 4 ,3
4 5 ,0
21
24
42
18
CY
1 7 ,5
4 3 ,2
26
CZ
1 9 ,7
5 4 ,8
35
EE
2 3 ,8
4 3 ,1
19
H U
2 2 ,6
4 8 ,3
26
LT
2 2 ,3
4 4 ,9
23
LV
2 3 ,6
4 4 ,1
20
M T
1 9 ,0
4 0 ,6
22
PL
1 8 ,6
5 1 ,0
32
SK
1 6 ,3
5 0 ,6
34
SI
2 1 ,4
5 5 ,6
34
EU 15
2 5 ,5
5 1 ,6
26
24
49
26
EU 10
1 9 ,6
5 0 ,4
31
EU 25
2 4 ,5
5 1 ,4
27
76
3.3.2.
The change in public pension expenditure and its driving factors
3.3.2.1.
Peaks in public pension expenditures
The pressure for increased public pension spending over the projection period may vary for
different reasons, notably due to the retirement of the baby-boom generation. Many countries
see the peak in the level of public pension spending before the end of the projection period.
For instance, the peak in pension spending is around 2040 in BE, DK, FR, IT, NL and SE, and
already around 2030 in AT and FI. On the other hand, a number of countries face a growing
trend in public pension expenditure up to the end of the projection period of 2050, such as
DE, ES, IE, LU, PT and UK.
Table 3-7 Peaks in public pension expenditure as a share of GDP
C ountry
S tarting year
P eak year
V alue
2042
15,7
2004
BE
10,4
D ifference: from 2004 to the peak
A bsolute
%
5,3
51,5
CZ
8,5
2050
14,0
5,6
66,1
DK
9,5
2039
13,5
4,0
42,1
DE
11,4
2050
13,1
1,7
15,2
EE
6,7
2006
7,7
1,0
15,4
GR
ES
8,6
2046
16,2
7,6
88,6
FR
12,8
2040
15,0
2,1
16,6
134,8
IE
4,7
2050
11,1
6,4
IT
14,2
2039
15,9
1,7
11,7
CY
6,9
2050
19,8
12,9
188,5
LV
6,8
2004
6,8
0,0
0,0
LT
6,7
2050
8,6
1,8
27,3
LU
10,0
2047
17,7
7,7
77,1
HU
10,4
2050
17,1
6,7
64,8
MT
7,4
2021
10,2
2,8
37,6
NL
7,7
2039
11,7
3,9
50,7
AT
13,4
2033
14,1
0,7
5,2
PL
13,9
2004
13,9
0,0
0,0
PT
11,1
2050
20,8
9,7
87,8
SI
11,0
2050
18,3
7,3
66,4
SK
7,2
2050
9,0
1,8
24,7
FI
10,7
2033
14,1
3,4
32,0
SE
10,6
2040
11,6
1,0
9,1
6,6
2050
8,6
2,0
29,8
22,5
UK
E U 15
1)
10,6
2043
13,0
2,4
E U 10
E U 12 1)
10,9
2050
11,1
0,3
2,5
11,5
2044
14,3
2,7
23,8
1)
10,6
2044
12,8
2,2
21,0
E U 25
1) excluding G reece
For the EU10 Member States, one has to look at total pension spending in order to get a
picture of the path of the demographic pressure (see Table 3-17). In most of the EU10
Member States, demographic pressures will materialise only during the later part of the
projection period and the main increase in pension spending will be seen over the period
2030-2050. A growing trend in total pension spending up to the end of the projection period is
projected in CY, LT, HU, SK and SI. In Malta, the peak in pension spending does not match
that of the demographic pressures. The decrease in pension spending after the peak year of
2021 is driven by the parameters of the pension system, which will lead to virtually no real
increase in average pensions and a sharp decrease in the benefit ratio (that is the average
77
pension relative to output per worker), while the dependency ratio will remain on an
increasing trend over the whole projection period.
3.3.2.2.
The taxation of pensions
The comparison of the level of gross pension spending across countries is distorted by the fact
that Member States tax pension benefits differently. While countries such as Denmark and
Sweden tax pensions almost in the same way as wages, with a tax rate of 27% in 2004, no
taxes are levied on pensions in Lithuania, Slovenia and Slovakia. Also in the Czech Republic
and Estonia public pensions and in the United Kingdom state pensions are in practice tax-free
because the tax threshold is set at such a level that only a very small number of public
pensions are subject to taxes. In a large group of countries (DE, ES, FR, IT, LU, AT, PL, PT),
taxes levied on pensions are in the range of 5-15%, and in Finland and the Netherlands about
19%.
Graph 3-1 Gross and net public pension expenditure as a share of GDP in 2004
16,0
14,0
12,0
% of GDP
10,0
8,0
6,0
4,0
2,0
0,0
BE
CZ
DK
DE
EE
GR
ES
FR
IE
IT
CY
LV
LT
Gross
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
Net
Graph 3-1 provides an approximation of the impact of income taxes levied on pensions. It
should be noted that Member States may have applied different methods in estimating the
average effective tax rate on pensions. It was generally assumed that, unless there will be a
clear change to the current tax regime of pensions, the same effective tax rate can be applied
over the whole projection period. In fact, only Germany and Hungary indicated a change in
the tax regime: in both of the countries, this would lead to an increase in the taxation of public
pensions; in Germany, from an average tax rate of 12% in 2004 to 17% in 2050, when both
taxes and social security contributions are considered; in Hungary, the taxation will be
introduced in 2013, leading from the current zero level of taxation to a 15% tax rate in 2050,
thereby pushing also the gross level of pension expenditure upwards. Some countries (BE, IE,
CY, MT and UK) did not provide estimates on net pension expenditure developments.
78
Taking the taxation of public pensions into account, the differences in the levels of spending
are equalised to some degree, as the countries with the highest level of pension spending tend
to tax pensions while those with the lowest level of pension spending do not. Also the
projected increases in net pension spending are slightly lower than in gross spending in the
countries where the taxation matters, even notably lower in Germany and Hungary. In
contrast, Portugal and Slovenia stand out in that they have, already at the beginning of the
projection period, relatively high levels of pension spending and the highest increases. As
there is no taxation on pensions in Slovenia and only a light taxation in Portugal, at the end of
the projection period, their net spending on pensions would be by far the highest of all EU
countries.
3.3.2.3.
Old-age and early pensions
In order to have a better understanding of the importance of demographic pressures, and to
examine the effect of pension policies to reduce the take-up of disability pensions, it is
important to separately analyse the developments of old-age pensions and other (disability
and survivors’) pensions. In this exercise, it was aimed to separate old-age and early pensions
from others on the basis of the age of the pension beneficiary rather than according to the type
of the pension in the national scheme. In particular, in some Member States, the type of the
pension (i.e. disability pension) remains unchanged irrespective of the fact that the pensioner
reaches the statutory old-age retirement age. The purpose of categorising more closely
according to the age was to include in old-age and early pensions, all pensions that can be
considered as age-related pensions and, thus, their evolution is mainly driven by the age. It
was instructed to include in this category all pensions that are provided to persons above the
statutory old-age pension age and that are provided to persons in the age bracket typical for
early pensions (usually 55-64 years) if these pensions could be considered as substitutes for
early retirement pensions as it is often the case regarding disability pensions.
While there are differences across Member States as to how much pensions other than old-age
pensions are provided, there are also differences in the data availability as to how well old-age
and early pensions can be separated from other pensions. For instance, the French pension
schemes mainly provide only old-age pensions, whilst disabled people are entitled to sickness
benefits rather than disability pensions. Although such pensions have existed, their share in
the total number of pensions has been very small and they have not been shown separately in
the statistics41. Furthermore, in many countries, there have been problems to apply the agreed
common age brackets for the disaggregation of pensions. Germany, France, Cyprus and
Slovenia did not break down public pensions into the requested categories. All public
pensions are thus included in the category of ‘old-age and early pensions’. The UK did not
provide data on public disability benefits.
Table 3-2 reports in detail how Member States have applied the break-down between old-age
and early pensions, on one hand, and other pensions, on the other hand. It is thus obvious that
the share of old-age and early pensions in total public pensions shown in Table 3-8 is not fully
comparable across countries, but it might be indicative as to the extent to which the ageing of
the population influences the total public pension expenditure. Also, the projected
development over time can be considered to provide a picture of the changes in national
pension provisions as to the role of old-age pensions, on the one hand, and that of other
pensions, on the other hand.
41
For instance, Slovenia reported that disability pensions account for 3% of all pensions.
79
Table 3-8 Old-age and early pensions, gross, as a share of all public pensions
Old-age and early pensions, gross / Public pensions, gross
Country
2004
2010
2015
2020
2025
2030
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
3
BE
92
92
93
94
94
95
96
96
3
1
CZ
90
91
91
91
90
91
93
94
1
3
4
DK
DE 2)
77
81
83
83
83
84
85
84
8
-1
7
100
100
100
100
100
100
100
100
0
0
0
EE
89
88
88
88
88
89
89
90
0
2
2
13
GR
ES
FR 2)
65
65
65
66
68
71
76
78
6
7
100
100
100
100
100
100
100
100
0
0
0
IE
74
76
79
81
82
84
86
88
10
5
15
IT
CY 2)
98
98
98
98
99
99
99
99
1
0
1
100
100
100
100
100
100
100
100
0
0
0
LV
84
88
88
88
88
88
88
89
4
1
4
LT
85
85
85
85
86
86
86
86
1
0
1
LU
61
62
64
68
72
75
79
80
15
5
19
HU
80
81
86
90
90
90
92
92
10
2
12
MT
52
59
65
69
73
76
83
92
24
16
40
20
NL
64
68
72
75
78
80
84
83
17
3
AT
84
85
87
88
89
90
91
92
7
2
9
PL
77
83
84
86
87
86
83
82
9
-3
5
PT
SI 2)
78
79
80
82
82
82
82
83
4
0
5
100
100
100
100
100
100
100
100
0
0
0
SK
75
71
67
66
65
65
67
70
-11
5
-5
FI
74
79
81
83
85
86
87
88
12
2
14
SE
74
76
80
82
83
85
88
88
11
4
15
UK
EU15 1)
100
100
100
100
100
100
100
100
0
0
0
96
97
97
97
97
97
98
98
1
0
1
EU10
EU12 1)
81
84
85
87
88
87
87
88
6
1
7
94
94
95
95
95
96
96
96
2
0
2
EU25 1)
96
96
96
96
97
97
97
97
1
0
2
1) excluding Greece
2) DE, FR, CY and SI: no break-down according to the type of pension has been provided.
It can be seen that there is a general tendency towards an increasing share for old-age
pensions. This is a consequence of demographic developments and, secondly, a consequence
of pension policies that aim to reduce the use of disability pension schemes as substitutes for
early pensions and to redirect their use to genuine disability cases. Large increases in the
share of old-age pensions are projected in the Netherlands (+20 p.p.), Luxembourg (+19p.p.),
Ireland and Sweden (+15 p.p.), Finland (+14 p.p.), Spain (+13 p.p.) and Hungary (+12 p.p.)42.
Only in Slovakia is the share of public old-age pensions projected to decrease. However, this
development must be attributed primarily to the partial switch of old-age pensions to a private
scheme while disability pensions will remain in the public system.
42
The share of old-age pensions is projected to increase by 40 percentage points in Malta. However, this
figure is largely driven by the break-down applied, the category of old-age pensions was limited to main
schemes while other pensions included also specific pensions - but rather equivalent to old-age pensions
- being phased out over a transition period.
80
3.3.2.4.
Disability and survivors’ pensions
Looking at the evolution of disability and survivors’ pensions43 provides insights into the
projected impact of pension reforms with the aim of tightening access to disability pensions in
particular. In most cases, where a significant decrease in other pension expenditure is
projected, the access to disability pension schemes has been tightened and its use as a
substitute for an early pension reduced. In addition, in some countries, in particular in
Sweden, the provision of widows’ pensions will be phased out. A significant decrease in these
pensions is projected for Poland (by 1.8 percentage points of GDP), Sweden (by 1.5 p.p.),
Austria44 (by 1.2 p.p.), Finland (by 1.1 p.p.), the Netherlands (by 1 p.p.) and Hungary (by 0.8
p.p.)45. Public spending on disability and survivors’ pensions is projected to increase only in
Portugal (by 1.2 p.p.), Slovakia (by 0.9 p.p.), Spain (by 0.5 p.p.) and Lithuania (by 0.2p.p.). In
particular, in Lithuania, the projected increase reflects recent measures, which made the
disability pension more accessible.
Table 3-9 Disability and survivors’ pensions as a share of GDP between 2004 and 2050
Other pensions (disability, survivors), gross as % of GDP
Country
2004
2010
2015
2020
2025
2030
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
BE
0,8
0,8
0,8
0,8
0,7
0,7
0,7
0,7
-0,1
-0,1
-0,1
CZ
0,8
0,8
0,8
0,8
0,9
0,8
0,8
0,8
0,0
-0,1
-0,1
DK
2,2
1,9
1,9
1,9
2,0
2,0
2,0
2,1
-0,2
0,1
-0,1
0,8
0,8
0,7
0,6
0,6
0,5
0,5
0,4
-0,2
-0,1
-0,4
3,0
3,1
3,1
3,2
3,3
3,4
3,6
3,5
0,5
0,0
0,5
IE
1,3
1,2
1,3
1,3
1,3
1,3
1,3
1,3
0,0
0,0
0,0
IT
0,3
0,3
0,2
0,2
0,2
0,2
0,2
0,2
-0,1
0,0
-0,1
LV
1,1
0,6
0,6
0,6
0,6
0,7
0,7
0,6
-0,4
-0,1
-0,4
LT
1,0
1,0
1,0
1,0
1,1
1,1
1,2
1,2
0,1
0,1
0,2
LU
3,9
3,7
3,9
3,9
3,9
3,7
3,6
3,5
-0,3
-0,2
-0,5
HU
2,1
2,1
1,6
1,3
1,2
1,3
1,3
1,3
-0,7
0,0
-0,8
MT
3,6
3,6
3,5
3,2
2,7
2,2
1,3
0,5
-1,4
-1,6
-3,0
NL
2,8
2,4
2,3
2,3
2,2
2,1
1,9
1,9
-0,7
-0,2
-1,0
AT
2,2
1,9
1,7
1,6
1,5
1,3
1,2
0,9
-0,8
-0,4
-1,2
PL
3,2
2,0
1,6
1,3
1,3
1,3
1,5
1,4
-1,9
0,1
-1,8
PT
2,4
2,5
2,5
2,6
2,7
2,8
3,3
3,6
0,4
0,8
1,2
SK
1,8
1,9
2,1
2,3
2,5
2,7
2,7
2,7
0,9
0,0
0,9
FI
2,8
2,4
2,3
2,2
2,1
2,0
1,8
1,7
-0,8
-0,3
-1,1
-1,5
DE
EE
GR
ES
FR
CY
SI
SE
2)
UK
2,8
2,4
2,1
1,9
1,8
1,7
1,4
1,3
-1,1
-0,4
1)
1,8
1,7
1,6
1,6
1,6
1,6
1,6
1,5
-0,1
-0,1
-0,2
EU10 1)
2,2
1,6
1,4
1,3
1,3
1,3
1,4
1,3
-0,9
0,0
-0,9
EU12 1)
1,6
1,6
1,6
1,6
1,6
1,6
1,6
1,5
0,0
-0,1
-0,1
EU25 1)
1,8
1,7
1,6
1,6
1,6
1,6
1,6
1,5
-0,2
-0,1
-0,3
EU15
1) excluding countries which have not provided data or been able to show this catecory separately
2) UK: no data provided on disability benefits
43
The caveats concerning the separation of disability and survivors’ pensions described in the context of
Table 3-8 apply to this table, too.
44
AT: The figures of this table include only survivors’ pensions.
45
MT: the category includes also pensions other than disability pensions, cf. footnote 42.
81
3.3.2.5.
The factors driving the change in pension spending
The factors driving the increases in pension spending can be further analysed by decomposing
the results of the projections into four main explanatory factors, namely:
•
A dependency effect (or a population ageing effect), which measures the changes in
the dependency ratio over the projection period as the ratio of persons aged 65 and
over to the population aged 15 to 64;
•
an employment effect which measures changes in the share of the population of
working age (15 to 64) relative to the number of the employed, i.e. an inverse
employment rate;
•
a take-up effect of pensions46, which measures changes in the share of pensioners
relative to the population aged 65 and over. In effect, it measures the take-up of
pensions relative to the number of old people. For some countries, the reported
number of pensioners represents the number of pensions rather than the number of
pensioners. However, this bias should not affect the evolution in the take-up ratio over
time;
•
a benefit effect, which captures changes in the average pension relative to output per
employed person. Average pension and output per worker, approximating the average
wage, are measured each year of the projection exercise for the total population of
pensioners and employees. Thus, the benefit ratio also captures changes in the
structure of the respective population groups, in addition to the assumed increases in
pensions due to the indexation rules, the maturation of the pension system and longer
contribution periods as well as in wages due to the assumptions of labour productivity
growth rates. In particular, it should be noted that the benefit ratio does not measure
the level of the pension for any individual relative to his/her own wage and, hence, is
not equivalent to a replacement rate indicator47.
The following equation is used:
PensExp = Pop>65 x Pop (15-64) x PensNo x PensExp/PensNo
GDP
Pop(15-64)
EmplNo
Pop>65
GDP/EmplNo
The following tables (Table 3-10 and Table 3-12) decompose the projected change in public
spending, as a per cent of GDP, into the changes in the dependency ratio, employment rate,
take-up ratio of pensions and benefit ratio. Further tables (Table 3-13 and Table 3-14) present
then the contributions in terms of the increase in pension spending over the whole projection
period relative to spending in 2004. The contributions of the different factors to the changes in
pension spending have been measured as the sum of changes over 5-year periods in order to
reduce the magnitude of the residual component. Table 3-15 presents annual growth rates in
pension spending over selected time periods.
46
47
This effect is also known as ‘eligibility effect’ in the literature.
Table 2-2 of the Annex presents the gross and net replacement ratios of pensions calculated for a
hypothetical individual with a full career of 40 years at average earnings.
82
Table 3-10 The contribution of the decomposed factors to the change (in percentage
points) in all public pensions relative to GDP
D u e to g r o w th in :
P u b l ic p e n s io n s ,
g ro s s a s % o f G D P
Dependency
r a t io
s ta r t le v e l
2005
2)
E m p lo y m e n t
r a te
Take up
B e n e f it r a t io
r a t io
p .p . c h a n g e
P o p (6 5 + )
E m p lo y e d
P e n s io n e r s
A v e r a g e p e n s io n
2 0 0 5 -5 0
P o p (1 5 - 6 4 )
P o p ( 1 5 -6 4 )
Pop65+
G D P p e r w o rk e r
In t e r a c ti o n
e f fe c t
(r e s id u a l)
BE
1 0 ,4
5 ,1
7 ,7
- 1 ,5
-0 ,4
-0 ,6
- 0 ,1
DK
9 ,6
3 ,2
7 ,2
- 0 ,4
-2 ,8
-0 ,5
- 0 ,3
DE
1 1 ,1
1 ,9
7 ,5
- 1 ,1
-0 ,6
-3 ,5
- 0 ,4
GR
:
ES
8 ,7
7 ,0
1 2 ,4
- 1 ,8
-2 ,3
-0 ,8
- 0 ,4
FR
1 2 ,8
2 ,0
8 ,7
- 0 ,9
-1 ,8
-3 ,5
- 0 ,5
IE
4 ,6
6 ,5
7 ,9
- 0 ,5
-1 ,4
0 ,8
- 0 ,2
IT
1 4 ,3
0 ,4
1 1 ,5
- 2 ,0
-3 ,2
-5 ,3
- 0 ,7
LU
1 0 ,0
7 ,4
7 ,2
- 4 ,4
2 ,5
2 ,1
0 ,0
NL
7 ,4
3 ,8
6 ,3
- 0 ,2
-1 ,6
-0 ,4
- 0 ,3
AT
1 3 ,2
- 1 ,0
1 1 ,3
- 1 ,3
-5 ,8
-4 ,3
- 0 ,8
PT
1 1 ,5
9 ,3
1 3 ,7
- 0 ,2
-0 ,9
-3 ,0
- 0 ,4
FI
1 0 ,4
3 ,3
8 ,8
- 0 ,9
-3 ,1
-0 ,9
- 0 ,6
SE
1 0 ,4
0 ,9
4 ,8
- 0 ,6
-0 ,2
-2 ,8
- 0 ,2
UK
6 ,7
1 ,9
4 ,7
- 0 ,1
CY
7 ,0
1 2 ,8
1 0 ,2
- 1 ,2
1 ,2
2 ,5
0 ,1
CZ
8 ,5
5 ,6
1 0 ,5
- 0 ,3
-3 ,5
-0 ,6
- 0 ,6
EE
7 ,1
- 3 ,0
3 ,1
- 0 ,6
-1 ,5
-3 ,8
- 0 ,2
HU
1 0 ,7
6 ,4
1 0 ,5
- 1 ,1
-4 ,5
2 ,0
- 0 ,4
LT
6 ,7
1 ,9
5 ,4
- 1 ,0
-2 ,1
-0 ,2
- 0 ,2
LV
6 ,4
- 0 ,9
3 ,4
- 0 ,7
-1 ,3
-2 ,4
0 ,0
MT
7 ,5
- 0 ,5
7 ,3
- 1 ,2
-1 ,0
-5 ,0
- 0 ,6
PL
1 3 ,7
- 5 ,7
1 0 ,4
- 3 ,2
-4 ,5
-7 ,5
- 0 ,8
SK
7 ,4
1 ,5
9 ,0
- 1 ,3
-2 ,5
-3 ,1
- 0 ,6
1 1 ,0
7 ,3
1 3 ,3
- 1 ,0
-3 ,6
-0 ,9
- 0 ,6
1 0 ,5
2 ,3
8 ,2
- 1 ,0
-1 ,7
-2 ,8
- 0 ,4
1 1 ,5
0 ,3
9 ,9
- 1 ,7
-3 ,8
-3 ,5
- 0 ,6
1 0 ,6
2 ,7
9 ,3
- 1 ,3
-1 ,8
-3 ,1
- 0 ,4
1 0 ,6
2 ,2
8 ,6
- 1 ,1
-2 ,1
-2 ,7
- 0 ,4
SI
EU 15
1)
EU 10
EU 12
1)
EU 25
1)
- 2 ,6
1 ) e x c lu d in g c o u n trie s w h ic h h a v e n o t p r o v id e d in fo rm a tio n
2 ) T h e b a s e y e a r o f th e d e c o m p o s itio n c a lc u la tio n s is 2 0 0 5 ( in s te d o f 2 0 0 4 in o th e r ta b le s ) b e c a u s e th e c h a n g e s h a v e b e e n m e a s u r e d
a s th e s u m o f c h a n g e s o v e r 5 - y e a r p e r io d s .
Table 3-10 shows the impact of the decomposed factors in terms of percentage point changes
in public pension expenditure relative to GDP. The findings can be summarised as follows:
•
In almost all countries, the old-age dependency ratio weighs on the increase in pension
spending by far more than the total increase, while the other factors offset part of the
increase coming from the ageing of the population. The strongest offsetting effect
comes from the benefit ratio and in the EU10 Member States also from the eligibility
ratio.
•
Demographic change alone, measured by the dependency ratio, would result in
expenditure increases by over 10 percentage points of GDP in Spain, Italy, Austria,
Portugal, Cyprus, the Czech Republic, Hungary, Poland and Slovenia. On average, in
the EU15, the demographic pressure alone would push public pension spending
upwards by over 8 percentage points of GDP and in the EU10 by almost 10
percentage points.
83
•
The offsetting factors, notably the projected reduction in the benefit ratio, are
projected to have a very large impact on the increase. In the EU15, these factors are
expected to offset some 70% of the pressure caused by demographic development
alone and in the EU10 almost all the pressure.
•
The contribution of the relative benefit ratio reflects for a number of countries
institutional changes, notably the partial switch of social security pensions into private
schemes (PL, SK, LV and EE). Secondly, it reflects the change in the indexation rules
of pensions. If the indexation of pensions is shifted towards prices only, the average
benefit to average output per employee (average wage) will decrease over time. The
earlier switch to price indexation of pension in Italy and the recently reformed
indexation rules in Germany, France and Austria explain the relatively large offsetting
impact of the relative benefit ratio on the pension expenditure increase. In the case of
Malta, the indexation of the maximum pension to a price index explains a large
decrease in the relative benefit ratio. In contrast, subjecting pensions more to taxes, as
in Hungary, will increase the gross pension, which is measured by the benefit ratio,
but not to the same degree the net pension. The level of pensions relative to wages
(approximated by output per employee is projected to increase also in Ireland,
Luxembourg and the most strongly in Cyprus, reflecting largely the maturation of
their pension systems, which takes account of longer careers with contributions paid to
the system.
•
Large decreases in the take-up ratio of pensions are projected in particular for Austria,
Hungary and Poland but also in the Czech Republic, Italy, Finland and Slovenia.
These reflect changes in pension policies that have aimed at increasing the effective
retirement age either through increases in the statutory retirement age and/or through
tightening access to early and disability pension schemes. In contrast, the number of
pensioners relative to the number of older people in the population is projected to
remain, by and large, unchanged in Belgium, Germany and Sweden. However, this
may include structural changes in the take-up of pensions, for instance, a higher takeup of pensions by women thanks to their increasing participation in the labour market
and a lower take-up of pensions by men due to reforms undertaken.
•
Employment rates are projected to increase in all countries and, consequently, this
would help to offset some of the demographic pressures on pension expenditure.
Particularly large contributions from higher employment are projected for Poland.
Other countries with relatively low current employment rates such as Spain, Belgium,
Italy, Austria and Slovakia are also projected to get relief from higher employment
rates. In the remaining countries, the offsetting impact of employment is projected to
be about one percentage point or less.
•
In Luxembourg, the pressure on public pension spending coming from changes in
dependency ratio, employment rate and eligibility rate should be considered together
because a considerable part of the labour supply is provided by cross-border workers,
making the trends of the employed persons and the resident population inconsistent
with each other. Thus, the population components alone do not reflect correctly the
driving forces of pension expenditure developments, while the three components
together reflect the evolution of the number of persons accruing pension rights in the
system.
84
Table 3-11 The projected benefit ratio: average public pension relative to output per
worker
Benefit ratio: Average public pension relative to output per worker
p.p. change
p.p. change
p.p. change
Country
2004
2010
2015
2020
2025
2030
2040
2050
2004-2030
2030-2050
2004-2050
BE
17,7
17,8
17,8
17,8
17,6
17,4
16,9
16,4
-0,3
-1,0
-1,3
CZ
15,7
14,1
13,5
13,2
13,0
13,1
13,7
14,1
-2,7
1,0
-1,7
DK
20,2
19,9
19,5
19,4
19,3
19,2
19,0
19,2
-1,0
0,0
-1,1
DE
18,5
16,6
16,6
16,2
15,6
14,8
13,9
13,3
-3,6
-1,5
-5,2
EE
10,5
11,3
10,2
9,0
8,0
7,2
6,2
5,3
-3,4
-1,9
-5,3
GR
ES
17,2
19,6
19,1
18,9
19,0
19,1
18,8
17,1
2,0
-2,0
-0,1
FR
24,4
24,1
23,0
22,0
21,1
20,3
19,3
18,9
-4,2
-1,3
-5,5
IE
14,3
14,9
15,9
16,2
16,6
16,5
16,1
15,7
2,2
-0,8
1,4
IT
20,0
20,8
20,4
19,8
18,8
17,7
15,7
14,0
-2,2
-3,7
-6,0
CY
25,6
28,6
27,9
26,9
25,5
25,7
28,9
30,8
0,1
5,1
5,2
LV
11,4
9,9
9,4
9,2
9,1
9,1
8,9
7,2
-2,2
-1,9
-4,2
-0,1
LT
7,7
7,9
8,1
8,4
8,6
8,4
8,0
7,5
0,8
-0,9
LU
23,5
23,4
24,7
25,0
26,4
26,6
27,5
28,0
3,1
1,4
4,5
HU
13,4
14,4
14,7
15,3
15,5
15,6
16,1
16,2
2,3
0,5
2,8
MT
18,4
19,9
20,1
19,0
17,2
15,2
12,4
10,3
-3,2
-4,9
-8,1
NL
19,5
18,8
18,6
18,4
18,2
18,1
18,0
18,1
-1,4
0,0
-1,4
AT
21,8
21,4
21,0
20,6
19,9
19,0
16,7
15,2
-2,8
-3,8
-6,6
PL
25,0
24,1
21,1
19,7
18,4
16,9
13,8
10,7
-8,1
-6,2
-14,3
PT
18,6
18,4
18,1
17,9
17,2
16,5
15,9
15,4
-2,1
-1,0
-3,2
SI
18,9
18,5
18,0
17,7
17,4
17,3
17,2
17,3
-1,6
0,0
-1,6
-4,2
SK
13,0
12,6
12,4
12,3
12,0
11,4
9,9
8,8
-1,7
-2,6
FI
19,8
19,6
19,4
19,1
18,8
18,5
18,3
18,0
-1,3
-0,5
-1,9
SE
21,3
20,0
18,7
17,5
16,9
16,5
16,2
15,9
-4,8
-0,6
-5,4
EU15 1)
22,6
22,1
21,6
21,0
20,3
19,6
18,4
17,6
-3,0
-2,0
-5,0
EU10 1)
18,2
17,8
16,6
16,2
15,7
15,1
14,1
12,8
-3,1
-2,3
-5,4
EU12 1)
20,2
19,9
19,5
19,0
18,4
17,6
16,5
15,6
-2,5
-2,0
-4,6
EU25 1)
21,7
21,4
21,0
20,4
19,8
19,1
18,0
17,0
-2,6
-2,2
-4,7
UK
1) excluding countries which have not provided data
Table 3-11 shows more specifically the evolution of the benefit ratios embedded in the
projections. Only four countries (CY, IE, LU and HU) project that average pension benefits
will increase relative to wages (approximated by output per employee). A projected decrease
in the benefit ratio mainly reflects that pensions in payment will not be raised at the same
pace as the wages increase. Among the EU15 Member States, particularly large decreases in
the benefit ratios are projected in countries that have already moved (Italy) or decided
recently to move to price indexation such as France and Austria48. However, the initial level
of benefits is at a relatively high level at the beginning of the projection period and the benefit
level at the end of the projection period would still be close to the EU average level. In
Germany, the sustainability factor as part of the indexation formula will reduce the relative
benefit level to about the same degree as the price indexation in some other countries. In the
EU10 Member States, the projected decrease is partially due to the indexation and partially
due to the switch to private schemes. For these countries, the level of public pensions alone
should not be interpreted as an indicator of the future pension generosity. The level of total
pensions is shown in Table 3-17 and the benefit ratio for total pensions in Table 3-18.
48
Table 2-3 of the Annex describes the indexation rules of Member States’ pension schemes.
85
Table 3-12 The contribution of the decomposed factors to the change (in percentage
points) in the public old-age and early pensions relative to GDP
D u e to g r o w th in :
O ld -a g e a n d e a r ly p e n s io n s ,
g ro s s a s % o f G D P
Dependency
r a t io
s ta r t le v e l
2005
2)
E m p lo y m e n t
r a te
Take up
B e n e f it r a t io
r a t io
p .p . c h a n g e
P o p (6 5 + )
E m p lo y e d
P e n s io n e r s
A v e r a g e p e n s io n
2 0 0 5 -2 0 5 0
P o p (1 5 - 6 4 )
P o p ( 1 5 -6 4 )
Pop65+
G D P p e r w o rk e r
In t e r a c ti o n
e f fe c t
(r e s id u a l)
BE
9 ,6
5 ,3
7 ,3
- 0 ,8
0 ,1
-1 ,2
- 0 ,1
DK
7 ,5
3 ,3
5 ,9
- 0 ,3
-1 ,6
-0 ,5
- 0 ,2
DE
1 1 ,1
1 ,9
7 ,5
- 1 ,1
-0 ,6
-3 ,5
- 0 ,4
GR
:
ES
5 ,7
6 ,6
8 ,9
- 1 ,2
0 ,0
-1 ,0
- 0 ,1
FR
1 2 ,8
2 ,0
8 ,7
- 0 ,9
-1 ,8
-3 ,5
- 0 ,5
IE
3 ,5
6 ,4
6 ,5
- 0 ,4
0 ,3
0 ,0
- 0 ,1
IT
1 4 ,0
0 ,5
1 1 ,4
- 2 ,0
-2 ,9
-5 ,3
- 0 ,7
LU
6 ,1
7 ,8
5 ,0
- 3 ,2
4 ,3
1 ,5
0 ,2
NL
4 ,8
4 ,6
4 ,6
- 0 ,2
0 ,0
0 ,1
0 ,0
AT
1 1 ,0
0 ,2
9 ,9
- 1 ,1
-4 ,5
-3 ,3
- 0 ,7
PT
9 ,0
8 ,1
1 1 ,2
- 0 ,1
0 ,4
-3 ,0
- 0 ,3
FI
8 ,0
4 ,0
7 ,1
- 0 ,7
-1 ,1
-0 ,9
- 0 ,4
SE
7 ,6
2 ,3
3 ,8
- 0 ,5
0 ,9
-1 ,7
- 0 ,1
UK
6 ,7
1 ,9
4 ,7
- 0 ,1
-0 ,7
-1 ,7
- 0 ,2
CY
7 ,0
1 2 ,8
1 0 ,2
- 1 ,2
CZ
7 ,6
5 ,6
9 ,6
- 0 ,3
-2 ,6
-0 ,6
- 0 ,5
EE
6 ,3
- 2 ,5
2 ,8
- 0 ,5
-1 ,1
-3 ,5
- 0 ,2
HU
8 ,6
7 ,2
9 ,3
- 0 ,9
-1 ,9
0 ,9
- 0 ,2
LT
5 ,7
1 ,7
4 ,6
- 0 ,9
-1 ,6
-0 ,3
- 0 ,2
LV
5 ,7
- 0 ,8
3 ,0
- 0 ,6
-1 ,0
-2 ,2
0 ,0
MT
3 ,9
2 ,6
4 ,8
- 0 ,7
2 ,6
-3 ,9
- 0 ,3
PL
1 1 ,1
- 4 ,5
8 ,7
- 2 ,6
-3 ,6
-6 ,2
- 0 ,8
SK
5 ,6
0 ,7
6 ,1
- 0 ,9
-1 ,5
-2 ,6
- 0 ,4
SI
1 1 ,0
7 ,3
1 3 ,3
- 1 ,0
-0 ,5
-4 ,0
- 0 ,6
- 0 ,3
EU 15
1)
EU 10
EU 12
1)
EU 25
1)
3 ,8
9 ,8
2 ,4
7 ,7
- 0 ,9
-1 ,2
-2 ,8
1 0 ,7
0 ,9
8 ,6
- 1 ,4
-2 ,8
-3 ,0
- 0 ,5
9 ,8
2 ,7
8 ,7
- 1 ,2
-1 ,4
-3 ,1
- 0 ,4
9 ,8
2 ,3
8 ,0
- 1 ,1
-1 ,5
-2 ,8
- 0 ,4
1 ) e x c lu d in g c o u n trie s w h ic h h a v e n o t p r o v id e d in fo rm a tio n
2 ) T h e b a s e y e a r o f th e d e c o m p o s itio n c a lc u la tio n s is 2 0 0 5 ( in s te d o f 2 0 0 4 in o th e r ta b le s ) b e c a u s e th e c h a n g e s h a v e b e e n m e a s u r e d
a s th e s u m o f c h a n g e s o v e r 5 - y e a r p e r io d s .
The main findings concerning the driving forces for the increase in public old-age and early
pensions can be summarised as follows:
•
as old-age pensions constitute the greatest share of all social security pensions, the
decomposition of the old-age pension expenditure increase confirms the findings for
all public pensions;
•
the main difference relative to the decomposition of the increase in all pensions comes
from the take-up ratio. In the case of the old-age pensions, the take-up ratio has a
smaller offsetting impact, reflecting a closer relationship between the number of oldage pensioners and the older population. This suggests that the gains in a lower takeup of pensions would result more from changes in the take-up of pensions other than
old-age pensions, i.e., among persons below the age of 65. This can be expected as a
consequence of increased statutory retirement ages and tightened access to early
retirement or pre-retirement pensions. Nevertheless, notable decreases in the take-up
ratio of old-age pensions are projected in particular in Austria, Poland, the Czech
Republic and Italy;
86
•
an increase in the take-up ratio reflects in the first instance the increasing number of
old-age people, due to larger age cohorts reaching the age of retirement and the
increasing longevity. This impact is particularly large in Malta, but positive also in
Belgium, Ireland, Portugal and Sweden. In some countries, in particular in Belgium,
Spain and Malta, this reflects the increase in the female participation rate and,
subsequently, the accrual of own pension rights of women and a higher number of
female pensioners. It could be noted that the number of pensioners may also include
persons receiving pensions abroad while they are excluded from the resident
population. In the Swedish case, this explains the rising eligibility ratio;
•
when only old-age pension spending is concerned, the demographic challenge is the
largest in Slovenia, Italy, Portugal and Cyprus.
The following tables present the decomposition effects in terms of the increase of pension
spending (in %) over the projection period relative to the spending in 2005. The findings
largely support those presented above by the analysis of the contribution to the percentage
point increase relative to GDP.
Table 3-13 Decomposition of the increase (in %) in public pension expenditure between
2005 and 2050
D u e to g r o w th i n :
P u b lic p e n s io n s ,
g ro s s a s % o f G D P
Dependency
r a tio
s t a r t le v e l
2005
2)
P o p (6 5 + )
% change 2005P o p (1 5 -6 4 )
50
E m p lo y m e n t
ra te
Take up
B e n e fit ra tio
ra tio
E m p lo y e d
P e n s io n e r s
A v e r a g e p e n s io n
P o p ( 1 5 -6 4 )
Pop65+
G D P p e r w o rk e r
In t e r a c ti o n
e f fe c t
(r e s i d u a l)
BE
1 0 ,4
4 9 ,7
6 1 ,6
-1 3 ,8
-2 , 4
-2 ,7
7 ,0
DK
9 ,6
3 3 ,3
6 5 ,1
-3 ,7
-2 4 , 1
-4 ,7
0 ,6
DE
1 1 ,1
1 7 ,4
6 5 ,8
-1 0 ,3
-5 , 6
-2 9 ,6
-2 ,8
GR
:
8 5 ,4
-1 6 , 1
1 4 ,9
ES
8 ,7
8 1 ,4
1 0 5 ,0
-1 9 , 7
-1 7 , 5
-1 ,3
FR
1 2 ,8
1 5 ,4
6 3 ,6
-7 ,0
-1 2 ,9
-2 5 ,7
-2 ,6
IE
4 ,6
1 4 1 ,9
1 0 7 ,0
-9 ,9
-2 0 , 7
1 9 ,3
4 6 ,2
IT
1 4 ,3
2 ,8
7 8 ,5
-1 3 , 8
-2 1 , 4
-3 5 ,3
-5 ,1
LU
1 0 ,0
7 3 ,7
5 6 ,3
-3 1 , 1
1 6 ,2
1 6 ,7
1 5 ,6
NL
7 ,4
5 1 ,4
7 1 ,9
-2 ,1
-1 9 , 3
-4 ,3
5 ,1
AT
1 3 ,2
-7 ,5
8 4 ,5
-1 0 ,1
-4 3 , 3
-3 2 ,3
-6 ,4
PT
1 1 ,5
8 0 ,3
8 8 ,5
-0 ,9
-3 ,9
-2 0 ,1
1 6 ,6
FI
1 0 ,4
3 2 ,0
7 2 ,9
-7 ,7
-2 5 ,2
-6 ,1
-1 ,8
SE
1 0 ,4
8 ,5
4 5 ,6
-6 ,2
-2 , 0
-2 6 ,7
-2 ,1
UK
6 ,7
2 8 ,3
6 4 ,2
-1 ,8
CY
7 ,0
1 8 3 ,5
9 4 ,4
-1 6 , 2
1 2 ,4
1 9 ,8
7 3 ,1
CZ
8 ,5
6 5 ,9
1 0 9 ,3
-3 ,6
-3 6 , 8
-9 ,0
6 ,1
EE
7 ,1
-4 1 , 4
6 0 ,3
-7 ,7
-2 6 ,8
-7 3 ,2
5 ,9
HU
1 0 ,7
6 0 ,1
7 9 ,4
-1 0 ,3
-3 3 , 4
1 6 ,3
8 ,1
LT
6 ,7
2 8 ,5
7 2 ,1
-1 6 , 0
-2 7 , 3
0 ,0
-0 ,2
LV
6 ,4
-1 3 , 4
6 2 ,7
-1 1 , 1
-2 0 , 6
-4 0 ,9
-3 ,5
MT
7 ,5
-6 ,4
8 0 ,8
-1 3 , 6
-1 0 , 5
-5 3 ,5
-9 ,5
PL
1 3 ,7
-4 1 , 7
1 0 8 ,3
-2 6 , 7
-4 3 , 7
-7 9 ,1
-0 ,5
-8 ,2
SK
7 ,4
2 0 ,3
1 2 2 ,0
-1 9 , 0
-3 4 , 0
-4 0 ,6
SI
1 1 ,0
6 6 ,2
9 9 ,7
-8 ,5
-2 6 ,8
-7 ,5
9 ,2
1 0 ,5
2 2 ,1
7 2 ,1
-9 ,3
-1 4 ,9
-2 4 ,1
-1 ,6
1 0 ,9
2 ,6
1 0 0 ,0
-1 6 , 9
-3 8 , 2
-3 4 ,8
-7 ,5
1 1 ,5
2 3 ,2
7 4 ,8
-1 1 ,0
-1 4 , 6
-2 4 ,3
-1 ,5
1 0 ,6
2 0 ,9
7 6 ,1
-1 0 ,8
-1 8 , 7
-2 3 ,5
-2 ,1
EU 15
1)
EU 10
EU 12
1)
EU 25
1)
1 ) e x c lu d in g c o u n t rie s w h ic h h a v e n o t p r o v id e d in f o rm a t io n
2 ) T h e b a s e y e a r o f t h e d e c o m p o s it io n c a lc u la t io n s is 2 0 0 5 ( in s t e d o f 2 0 0 4 in o t h e r t a b le s ) b e c a u s e t h e c h a n g e s h a v e b e e n m e a s u r e d
a s t h e s u m o f c h a n g e s o v e r 5 - y e a r p e r io d s .
87
Table 3-14 Decomposition of the increase (in %) in public old-age and early pension
expenditure between 2005 and 2050
D u e to g r o w th in :
O ld -a g e a n d e a r ly p e n s io n s ,
g ro s s a s % o f G D P
s t a r t le v e l
2005
2)
% change
2 0 0 5 -5 0
Dependency
r a tio
P o p (6 5 + )
P o p (1 5 -6 4 )
E m p lo y m e n t
Take up
B e n e fit ra tio
r a te
E m p lo y e d
ra tio
P e n s io n e r s
A v e r a g e p e n s io n
P o p (1 5 -6 4 )
Pop65+
G D P p e r w o rk e r
In t e r a c t i o n
e ffe c t
( r e s i d u a l)
BE
9 ,6
5 5 ,4
6 1 ,6
-8 ,2
1 ,8
-8 ,7
8 ,8
DK
7 ,5
4 3 ,7
6 5 ,1
-3 ,7
-1 5 ,8
-5 ,5
3 ,6
DE
1 1 ,1
1 7 ,4
6 5 ,8
-1 0 ,3
-5 ,6
-2 9 ,6
-2 ,8
GR
:
8 5 ,4
-1 6 ,1
3 2 ,7
ES
5 ,7
1 1 6 ,9
1 0 5 ,0
-1 9 ,7
5 ,3
-6 ,3
FR
1 2 ,8
1 5 ,4
6 3 ,6
-7 ,0
-1 2 ,9
-2 5 ,7
-2 ,6
IE
3 ,5
1 8 2 ,9
1 0 7 ,0
-9 ,9
3 ,1
1 1 ,1
7 1 ,7
IT
1 4 ,0
3 ,9
7 8 ,5
-1 3 ,8
-2 0 ,2
-3 5 ,5
-5 ,1
LU
6 ,1
1 2 8 ,6
5 6 ,3
-3 1 ,1
4 3 ,3
1 7 ,9
4 2 ,2
NL
4 ,8
9 4 ,8
7 1 ,9
-2 ,1
-0 ,1
1 ,3
2 3 ,6
AT
1 1 ,0
2 ,3
8 4 ,5
-1 0 ,1
-3 8 ,4
-2 7 ,5
-6 ,2
PT
9 ,0
8 9 ,8
8 8 ,5
-0 ,9
6 ,0
-2 4 ,7
2 0 ,7
FI
8 ,0
5 0 ,1
7 2 ,9
-7 ,7
-1 1 ,0
-8 ,0
3 ,9
SE
7 ,6
3 0 ,9
4 5 ,6
-6 ,2
1 0 ,7
-2 0 ,8
1 ,6
UK
6 ,7
2 8 ,3
6 4 ,2
-1 ,8
-9 ,9
-2 3 ,7
-0 ,6
CY
7 ,0
1 8 3 ,5
9 4 ,4
-1 6 ,2
CZ
7 ,6
7 3 ,8
1 0 9 ,3
-3 ,6
-3 0 ,2
-1 1 ,1
9 ,4
EE
6 ,3
-4 0 ,2
6 0 ,3
-7 ,7
-2 1 ,3
-7 6 ,3
4 ,8
HU
8 ,6
8 2 ,9
7 9 ,4
-1 0 ,3
-1 3 ,7
9 ,3
1 8 ,2
LT
5 ,7
3 0 ,0
7 2 ,1
-1 6 ,0
-2 3 ,9
-2 ,3
0 ,2
LV
5 ,7
-1 3 ,5
6 2 ,7
-1 1 ,1
-1 7 ,2
-4 3 ,9
-3 ,9
MT
3 ,9
6 5 ,1
8 0 ,8
-1 3 ,6
4 6 ,1
-5 1 ,7
3 ,7
PL
1 1 ,1
-4 0 ,9
1 0 8 ,3
-2 6 ,7
-4 1 ,2
-7 9 ,7
-1 ,5
-9 ,5
SK
5 ,6
1 2 ,1
1 2 2 ,0
-1 9 ,0
-3 1 ,3
-5 0 ,2
SI
1 1 ,0
6 6 ,2
9 9 ,7
-8 ,5
-3 ,6
-3 0 ,5
9 ,1
9 ,8
2 4 ,6
7 2 ,1
-9 ,2
-1 1 ,0
-2 6 ,2
-1 ,2
EU 15
1)
EU 10
EU 12
1)
EU 25
1)
9 ,1
9 ,5
1 0 0 ,0
-1 6 ,9
-3 2 ,8
-3 4 ,0
-6 ,8
1 0 ,7
2 5 ,2
7 4 ,8
-1 0 ,8
-1 1 ,6
-2 6 ,0
-1 ,1
9 ,8
2 3 ,6
7 6 ,1
-1 0 ,7
-1 4 ,2
-2 6 ,0
-1 ,6
1 ) e x c lu d in g c o u n t r ie s w h ic h h a v e n o t p r o v id e d in f o r m a t io n
2 ) T h e b a s e y e a r o f t h e d e c o m p o s it io n c a lc u la t io n s is 2 0 0 5 ( in s t e d o f 2 0 0 4 in o t h e r t a b le s ) b e c a u s e t h e c h a n g e s h a v e b e e n m e a s u r e d
a s t h e s u m o f c h a n g e s o v e r 5 - y e a r p e r io d s .
Table 3-15 analysis the time path of the projected increases in old-age pension spending and
how the different components influence these projected increases over selected time periods:
•
as the dependency ratio is the strongest driving force for increases in pension
spending, the time path of the increases is also dominated by this fact. Dependency
ratios have the largest impact in the period 2015-2030, in particular in the EU15
Member States, while in the EU10 Member States the impact is more evenly spread
over the whole projection period;
•
the employment rate and the eligibility rate are projected to have their largest
offsetting impact at the beginning of the projection period (2005-2015). This is a
credible result when bearing in mind that the labour force projections are based on an
assumption of unchanged policies and only the impact of the already legislated policy
changes is included;
•
the decrease in the benefit ratio is projected to be more evenly spread over the
projection period than the decreases in the employment and eligibility ratios, with
some tendency to strengthen over time. In particular, in the EU10 Member States, this
would reflect the maturation of the switch from public schemes to private ones.
88
Table 3-15 Annual growth rates of public old-age and early pensions over selected time
periods and decomposed by driving factors
Old-age and early pensions, gross as % of GDP
Dependency ratio
BE
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
DK
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
DE
Employment
Take up ratio
Benefit ratio
Interaction effect
2005 - 2015
2015 - 2030
2030 - 2050
2005 - 2030
2005 - 2050
0,69
1,03
-0,58
0,23
0,00
-0,01
2,07
2,33
-0,12
0,01
-0,18
-0,02
0,31
0,69
-0,02
-0,04
-0,30
0,01
1,51
1,81
-0,31
0,10
-0,11
-0,02
0,98
1,31
-0,18
0,04
-0,19
0,00
1,77
2,46
-0,28
-0,13
-0,27
0,01
1,29
1,80
0,01
-0,40
-0,11
0,01
-0,03
0,53
-0,05
-0,44
-0,06
0,00
1,48
2,06
-0,11
-0,29
-0,18
0,01
0,81
1,38
-0,08
-0,36
-0,12
0,01
-0,56
1,28
-0,90
-0,14
-0,79
0,01
1,02
2,26
-0,07
-0,39
-0,76
0,02
0,33
0,81
-0,01
0,07
-0,55
0,00
0,38
1,86
-0,40
-0,29
-0,77
0,02
0,36
1,40
-0,22
-0,13
-0,67
0,01
1,25
-1,54
1,77
0,07
2,15
-0,05
1,56
-0,57
1,82
-0,34
0,10
1,18
-1,64
0,20
0,36
-0,01
2,62
2,20
-0,07
0,56
-0,07
-0,01
1,90
2,74
-0,08
-0,26
-0,49
0,02
1,61
1,79
-0,70
0,41
0,10
0,00
1,74
2,21
-0,42
0,11
-0,16
0,01
0,27
1,51
-0,42
-0,18
-0,63
0,01
0,56
2,12
-0,13
-0,54
-0,86
0,03
0,16
0,71
-0,04
-0,16
-0,34
0,00
0,44
1,87
-0,25
-0,40
-0,77
0,02
0,32
1,36
-0,15
-0,29
-0,58
0,01
2,98
1,94
-0,70
-0,21
1,94
-0,01
2,33
2,36
-0,14
0,11
0,01
0,00
2,02
2,37
-0,03
0,17
-0,48
0,01
2,59
2,19
-0,36
-0,02
0,78
-0,01
2,34
2,27
-0,22
0,07
0,22
0,00
-0,28
1,50
-0,95
-1,01
0,18
0,01
0,60
1,75
-0,12
-0,05
-0,95
0,02
-0,12
1,70
-0,12
-0,48
-1,20
0,02
0,25
1,65
-0,45
-0,44
-0,50
0,01
0,08
1,67
-0,30
-0,46
-0,81
0,02
1,40
0,75
-0,60
0,57
0,67
0,00
3,24
2,19
-0,60
1,18
0,45
-0,02
1,05
0,68
-0,78
0,95
0,20
0,00
2,50
1,61
-0,60
0,94
0,54
-0,01
1,85
1,20
-0,68
0,94
0,39
-0,01
2,24
2,32
-0,01
-0,01
-0,06
0,00
2,42
2,41
-0,03
0,00
0,03
0,00
0,43
0,44
-0,07
0,00
0,07
0,00
2,35
2,38
-0,02
0,00
0,00
0,00
1,49
1,51
-0,05
0,00
0,03
0,00
-0,03
1,75
-0,78
-1,10
0,11
0,02
0,93
2,49
-0,08
-0,72
-0,73
0,03
-0,56
1,28
-0,05
-0,87
-0,91
0,01
0,54
2,19
-0,36
-0,87
-0,39
0,03
0,05
1,79
-0,22
-0,87
-0,63
0,02
1,17
1,35
-0,02
0,28
-0,45
0,00
1,74
2,06
0,00
0,50
-0,81
0,01
1,34
2,03
-0,04
-0,22
-0,42
0,01
1,51
1,78
-0,01
0,41
-0,66
0,01
1,43
1,89
-0,02
0,13
-0,56
0,01
Old-age and early pensions, gross as % of GDP
Dependency ratio
GR
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
ES
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
FR
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
IE
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
IT
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
LU
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
NL
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
AT
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
PT
Employment
Take up ratio
Benefit ratio
Interaction effect
89
Old-age and early pensions, gross as % of GDP
Dependency ratio
FI
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
SE
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
UK
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
CY
Employment
2005 - 2015
2015 - 2030
2030 - 2050
2005 - 2030
2005 - 2050
1,94
2,90
-0,47
-0,49
0,01
0,02
1,41
2,38
-0,17
-0,36
-0,42
0,02
0,01
0,19
-0,02
-0,05
-0,10
0,00
1,63
2,59
-0,29
-0,41
-0,24
0,02
0,91
1,52
-0,17
-0,25
-0,18
0,01
0,80
1,92
-0,51
0,37
-0,96
0,02
0,87
1,24
-0,03
0,42
-0,74
0,01
0,29
0,31
-0,03
0,03
-0,02
0,00
0,85
1,51
-0,22
0,40
-0,83
0,01
0,60
0,98
-0,14
0,24
-0,47
0,00
0,01
1,44
-0,10
-0,50
-0,81
0,01
1,09
1,91
-0,01
-0,29
-0,50
0,01
0,43
0,94
-0,03
-0,05
-0,43
0,00
0,66
1,72
-0,05
-0,38
-0,62
0,02
0,56
1,37
-0,04
-0,23
-0,54
0,01
2,36
2,21
-1,42
2,16
2,69
-0,17
2,47
1,38
0,05
2,24
2,50
-0,67
2,34
2,00
-0,35
-0,31
3,09
-0,43
-1,43
-1,46
0,07
1,10
2,19
-0,09
-0,71
-0,27
0,02
2,12
1,97
0,11
-0,32
0,35
0,00
0,54
2,55
-0,22
-1,00
-0,75
0,04
1,24
2,29
-0,08
-0,70
-0,26
0,02
-1,88
0,87
-0,88
-0,82
-1,06
-0,01
-1,50
1,60
0,02
-0,71
-2,38
0,03
-0,49
1,29
0,05
-0,14
-1,67
0,02
-1,65
1,31
-0,34
-0,75
-1,85
0,01
-1,14
1,30
-0,17
-0,48
-1,77
0,02
1,41
1,60
-0,87
0,14
0,54
0,00
1,34
1,85
-0,24
-0,43
0,17
0,01
1,33
1,61
0,11
-0,45
0,06
0,01
1,37
1,75
-0,49
-0,20
0,31
0,01
1,35
1,69
-0,22
-0,31
0,20
0,01
-0,11
0,72
-1,50
-0,05
0,71
-0,01
1,32
2,17
-0,17
-0,91
0,24
0,02
0,38
1,48
0,10
-0,51
-0,67
0,01
0,74
1,59
-0,70
-0,57
0,43
0,01
0,58
1,54
-0,34
-0,54
-0,06
0,01
-3,36
0,89
-1,38
-1,22
-1,70
-0,04
1,33
1,60
0,09
-0,25
-0,11
0,00
-0,01
1,40
0,09
-0,11
-1,36
0,02
-0,57
1,32
-0,49
-0,64
-0,75
0,01
-0,32
1,35
-0,24
-0,40
-1,02
0,01
4,85
2,98
-1,13
1,71
1,23
-0,05
0,65
2,26
-0,34
0,61
-1,83
0,04
-0,35
0,61
0,15
0,90
-1,99
0,03
2,31
2,55
-0,65
1,05
-0,62
0,01
1,12
1,68
-0,29
0,98
-1,23
0,02
-3,02
1,48
-1,76
-1,62
-1,15
-0,03
-0,26
3,38
-0,80
-1,48
-1,29
0,07
-0,89
1,80
0,19
-0,21
-2,63
0,05
-1,38
2,62
-1,18
-1,54
-1,24
0,04
-1,16
2,25
-0,57
-0,95
-1,86
0,04
-2,31
1,60
-1,52
-1,01
-1,39
-0,01
0,74
3,43
-0,57
-1,04
-1,03
0,06
1,20
2,37
0,27
-0,31
-1,11
0,03
-0,49
2,69
-0,95
-1,03
-1,17
0,04
0,25
2,55
-0,40
-0,71
-1,14
0,04
0,50
1,76
-0,72
0,38
-0,91
0,02
1,48
3,02
-0,09
-0,52
-0,89
0,04
1,20
1,61
0,01
0,02
-0,43
0,01
1,08
2,51
-0,34
-0,16
-0,89
0,03
1,14
2,11
-0,18
-0,08
-0,69
0,02
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
CZ
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
EE
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
HU
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
LT
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
LV
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
MT
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
PL
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
SK
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
SI
Employment
Take up ratio
Benefit ratio
Interaction effect
90
Old-age and early pensions, gross as % of GDP
Dependency ratio
EU15
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
EU10
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
EU12
Employment
Take up ratio
Benefit ratio
Interaction effect
Old-age and early pensions, gross as % of GDP
Dependency ratio
EU25
Employment
Take up ratio
Benefit ratio
Interaction effect
Legenda:
2005 - 2015
2015 - 2030
2030 - 2050
2005 - 2030
2005 - 2050
-0,04
1,45
-0,69
-0,34
-0,45
0,01
1,02
2,05
-0,07
-0,23
-0,71
0,02
0,36
1,22
-0,06
-0,22
-0,57
0,02
0,59
1,81
-0,32
-0,27
-0,61
0,02
0,49
1,54
-0,20
-0,25
-0,59
0,02
-1,35
1,68
-1,21
-1,12
-0,69
0,01
0,57
2,83
-0,50
-1,11
-0,60
0,04
0,71
1,78
0,16
-0,28
-0,93
0,02
-0,20
2,37
-0,78
-1,11
-0,64
0,03
0,20
2,11
-0,36
-0,75
-0,77
0,03
-0,07
1,42
-0,83
-0,33
-0,33
0,00
1,04
2,10
-0,08
-0,23
-0,74
0,02
0,38
1,31
-0,06
-0,25
-0,60
0,02
0,59
1,83
-0,38
-0,27
-0,57
0,01
0,50
1,60
-0,24
-0,26
-0,58
0,02
-0,12
1,49
-0,79
-0,46
-0,34
0,01
0,98
2,16
-0,14
-0,35
-0,67
0,02
0,38
1,30
-0,03
-0,23
-0,64
0,02
0,54
1,89
-0,40
-0,39
-0,54
0,02
0,47
1,63
-0,23
-0,32
-0,59
0,02
Dependency ratio = Pop 65+ / Pop (15-64)
Take up ratio = Pensioners / Pop 65+
3.3.3.
Employment = Employed / Pop (15-64)
Benefit ratio = Average pension / GDP per worker
Total pension expenditure
Public pensions are of great importance in all EU Member States and are even dominant in
the total pension provision of most countries. However, in a number of Member States, a
significant share of the pension provision comes from occupational and private statutory
schemes. And more importantly, their share of the total pension provision will increase in the
future.
Occupational pensions provide an equivalent to earnings-related social security schemes in
Denmark, the Netherlands, Ireland and the United Kingdom. In other countries, they
complement the earnings-related social security provision, thereby increasing the total level of
retirement income for pensioners. Furthermore, a part of the statutory social security pension
scheme has been switched into private schemes in a great number of countries. These
countries are: Estonia, Latvia, Lithuania, Hungary, Poland, Slovakia and Sweden.
Table 3-16 presents the projections of the Member States for occupational and private
statutory pensions. The projections of occupational pensions have been provided by the
Netherlands, Slovenia and Sweden. In the case of Sweden, the figures represent
complementary occupational pensions, while private statutory pensions are included in public
pensions. No projections of occupational pensions are presented for Denmark, Ireland and the
United Kingdom. The figures for the remaining countries in the Table 3-16 (EE, LV, LT, HU,
PL and SK) represent private statutory pensions.
91
Table 3-16 Occupational and private statutory pensions as a share of GDP between
2004 and 2050
Occupational and private mandatory pensions, gross as % of GDP
Country
2004
2010
2015
2020
2025
2030
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
0,0
0,1
0,2
0,3
0,6
1,3
2,4
0,6
1,8
2,4
0,0
0,1
0,2
0,4
1,1
2,7
0,4
2,3
2,7
0,0
0,1
0,2
0,4
1,0
1,8
0,4
1,4
1,8
0,0
0,1
0,2
0,5
1,6
3,1
0,5
2,7
3,1
4,7
5,2
5,8
6,7
7,7
9,0
8,7
3,1
1,0
4,1
0,0
0,0
0,1
0,2
0,3
0,7
1,3
0,3
1,1
1,3
0,0
0,1
0,2
0,3
0,7
1,0
0,3
0,7
1,0
0,0
0,1
0,2
0,4
0,7
1,4
2,3
0,7
1,6
2,3
2,3
2,5
2,5
2,6
2,8
2,9
2,6
0,5
-0,2
0,3
0,5
0,9
1,1
0,5
0,6
1,1
BE
CZ
DK
DE
EE
GR
ES
FR
IE
IT
CY
LV
LT
0,0
LU
HU
MT
NL
4,6
AT
PL
PT
SI
SK
FI
SE
2,3
UK
SE: private mandatory pensions (included in public pensions (Table 3- 3))
0,1
0,2
0,3
Occupational and private statutory pension provision will play an increasingly important role
over time in all countries where such provisions are in place. In particular, in the Netherlands,
occupational pensions are projected to amount to 8.7% of GDP in 2050, accounting for over
40% of the total pension provision. Private statutory pension schemes in the new Member
States are projected to increase the level of total pension expenditure by 1.3-3.1% of GDP at
the end of the projection period.
92
Table 3-17 Total pension expenditure as a share of GDP between 2004 and 2050
Total pension expenditure, gross as % of GDP
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
14,7
15,7
15,5
4,3
0,8
5,1
9,6
12,2
14,0
1,1
4,5
5,6
11,6
12,3
12,8
13,1
0,9
0,8
1,7
5,4
5,3
5,6
6,6
-1,4
1,3
-0,1
Country
2004
2010
2015
2020
2025
2030
BE
10,4
10,4
11,0
12,1
13,4
CZ
8,5
8,2
8,2
8,4
8,9
DE
11,4
10,5
10,5
11,0
EE
6,7
6,8
6,0
5,6
DK
GR
ES
8,6
8,9
8,8
9,3
10,4
11,8
15,2
15,7
3,3
3,9
7,1
FR
12,8
12,9
13,2
13,7
14,0
14,3
15,0
14,8
1,5
0,5
2,0
IE
IT
14,2
14,0
13,8
14,0
14,4
15,0
15,9
14,7
0,8
-0,4
0,4
CY
6,9
8,0
8,8
9,9
10,8
12,2
15,0
19,8
5,3
7,6
12,9
LV
6,8
4,9
4,6
5,0
5,6
6,0
7,0
8,3
-0,8
2,3
1,5
LT
6,7
6,6
6,6
7,1
7,8
8,3
9,2
10,4
1,6
2,1
3,7
7,4
LU
10,0
9,8
10,9
11,9
13,7
15,0
17,0
17,4
5,0
2,4
HU
10,4
11,1
11,6
12,6
13,3
13,9
17,6
20,3
3,6
6,3
9,9
MT
7,4
8,8
9,8
10,2
10,0
9,1
7,9
7,0
1,7
-2,1
-0,4
NL
12,4
12,3
13,6
14,8
16,4
18,4
20,6
20,0
6,0
1,5
7,6
AT
13,4
12,8
12,7
12,8
13,5
14,0
13,4
12,2
0,6
-1,7
-1,2
PL
13,9
11,3
9,8
9,8
9,7
9,4
9,3
9,3
-4,5
-0,1
-4,6
PT
11,1
11,9
12,6
14,1
15,0
16,0
18,8
20,8
4,9
4,8
9,7
SI
11,0
11,1
11,6
12,4
13,5
14,7
17,5
19,3
3,7
4,6
8,3
SK
7,2
6,7
6,7
7,2
7,8
8,3
9,7
11,2
1,2
2,9
4,1
FI
10,7
11,2
12,0
12,9
13,5
14,0
13,8
13,7
3,3
-0,3
3,1
SE
12,9
12,4
12,8
12,9
13,3
13,9
14,5
13,9
0,9
0,0
0,9
2,8
UK
EU15 1)
12,0
11,7
11,9
12,4
13,1
13,8
14,9
14,8
1,8
0,9
EU10
EU12 1)
10,9
9,8
9,3
9,6
9,9
10,1
11,4
12,6
-0,7
2,5
1,7
12,0
11,7
11,9
12,3
13,0
13,8
15,0
14,8
1,9
1,0
2,8
1)
11,9
11,6
11,7
12,2
12,8
13,5
14,6
14,6
1,6
1,1
2,7
EU25
1) excluding countries which have not provided data
The projections for total pension expenditure have been summed up from the data provided
for public, occupational and private statutory pensions. The sums are presented also for
countries which have not provided data on complementary occupational schemes if they are
not of major importance for total pension provision. Currently, such provision in many
countries is less than one percent of GDP and in some others around one percent of GDP. In
contrast, in Denmark and the United Kingdom, and to some extent also in Ireland,
occupational pension provision is clearly of greater importance and, consequently, the data
provided for public pensions only should not be considered as representing total pension
expenditure.
The projected total pension expenditure as a share of GDP in 2004 was the same as public
pension expenditure for all countries except those with occupational pensions (NL and SE)
because the private mandatory pensions were still at an early stage and virtually no pensions
have yet been paid out from those schemes. By 2050, the dispersion in pension provision
across countries will somewhat lessen, since many of those countries which have projected
very low public spending on pensions will have major private provisions.
Concerning the change in total pension expenditure as a share of GDP between 2004 and
2050, the negative change observed for public pensions in the case of Latvia and virtually also
in Estonia will disappear while the changes remain negative for Poland. Another major
change when compared with public pension spending is that the total pension expenditure in
the Netherlands, Hungary and Slovenia will become to the same level, about 20% of GDP,
with Portugal (20.8% of GDP) and Cyprus (19.8% of GDP).
93
Table 3-18 takes into account the impact of occupational and private mandatory pensions
showing the total benefit ratio, i.e. to the level of average total pensions relative to output per
worker. In particular, in the EU10 Member States, the decrease in the relative benefit level is
much smaller than for the relative level of public pensions alone (see Table 3-11). In fact,
total benefit levels are projected, by and large, to maintain their current levels relative to
earnings, except in Poland where a significant decrease is still projected. However, it should
be noted that the benefit ratio of public pensions to wages in Poland was the highest in the
whole EU in 2004.
Table 3-18 Benefit ratio: average total pension relative to output per worker
Benefit ratio: Average total pension relative to output per worker
p.p. change
p.p. change
p.p. change
Country
2004
2010
2015
2020
2025
2030
2040
2050
2004-2030
2030-2050
2004-2050
BE
17.7
17.8
17.8
17.8
17.7
17.4
16.9
16.4
-0.3
-1.0
-1.3
CZ
15.7
14.1
13.5
13.2
13.0
13.0
13.7
14.1
-2.7
1.0
-1.7
DE
18.5
16.6
16.6
16.2
15.6
14.8
13.9
13.3
-3.6
-1.5
-5.2
EE
10.5
11.4
10.3
9.3
8.5
8.1
8.1
8.3
-2.5
0.2
-2.2
ES
17.2
19.6
19.1
18.9
19.0
19.1
18.8
17.1
2.0
-2.0
-0.1
FR
24.4
24.1
23.1
22.0
21.1
20.3
19.3
18.9
-4.2
-1.3
-5.5
-6.0
DK
GR
IE
IT
20.0
20.8
20.4
19.8
18.8
17.7
15.7
14.0
-2.2
-3.7
CY
25.6
28.6
27.9
26.9
25.5
25.7
28.9
30.8
0.1
5.1
5.2
LV
11.4
9.9
9.4
9.4
9.5
9.8
10.6
10.7
-1.6
0.9
-0.7
4.5
LT
LU
23.5
23.4
24.7
25.0
26.4
26.6
27.5
28.0
3.1
1.4
HU
13.4
14.4
14.7
15.4
15.8
16.2
17.7
19.1
2.8
2.9
5.8
MT
18.4
19.9
20.1
19.0
17.2
15.2
12.4
10.3
-3.2
-4.9
-8.1
NL
29.2
27.6
27.9
28.2
28.5
29.2
30.3
30.4
0.0
1.3
1.2
AT
21.8
21.4
21.0
20.6
19.9
19.0
16.7
15.2
-2.8
-3.8
-6.6
PL
19.2
19.2
17.6
17.1
16.4
15.3
13.1
11.1
-3.9
-4.3
-8.2
PT
18.6
18.4
18.1
17.9
17.2
16.5
15.9
15.4
-2.1
-1.0
-3.2
SI
18.9
18.5
18.1
17.8
17.6
17.6
17.9
18.2
-1.2
0.6
-0.6
SK
13.0
12.7
12.7
12.7
12.7
12.4
11.6
11.0
-0.6
-1.4
-2.0
FI
19.8
19.7
19.4
19.1
18.8
18.5
18.3
18.0
-1.3
-0.5
-1.9
SE
25.9
24.6
23.2
21.7
21.0
20.7
20.2
19.6
-5.2
-1.1
-6.3
EU15 1)
20.3
19.6
19.1
18.5
17.9
17.2
16.3
15.4
-3.0
-1.9
-4.9
EU10 1)
17.2
17.2
16.5
16.4
16.1
15.7
15.2
14.7
-1.4
-1.1
-2.5
EU12 1)
20.6
20.3
19.9
19.4
18.8
18.1
17.0
16.0
-2.6
-2.0
-4.6
EU25 1)
19.3
19.0
18.6
18.1
17.6
17.0
16.1
15.1
-2.3
-2.0
-4.3
UK
1) excluding countries which have not provided data
94
Graph 3-2 below summarises the levels of expenditure on public, occupational and private
statutory pensions in 2004 and 2050.
Graph 3-2 Public, occupational and private mandatory pensions as a per cent of GDP in
2004, 2030 and 2050
25,0
20,0
15,0
10,0
5,0
BE
CZ
DK
DE
Public pensions
EE
GR
Occupational pensions
ES
FR
IE
IT
CY
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
0,0
LV
Private mandatory pensions, gross as % of GDP
25,0
20,0
15,0
10,0
5,0
LT
LU
HU
MT
Public pensions
NL
AT
Occupational pensions
PL
PT
SI
SK
FI
SE
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
2050
2030
2004
0,0
UK
Private mandatory pensions, gross as % of GDP
95
3.3.4.
Pensioners and contributors
The 2005 projections include information on the number of pensioners and contributors for
most countries. It should be noted, however, that in some countries (DE, ES, LT, LU, AT) the
number of pensioners represents the number of pensions rather than the number of pensioners.
This is due to the data sources used in the projections which often deal with (semi)aggregated data on pensions without attaching them to individuals, and the fact that in some
cases (notably in the case of old-age pensions and survivor’s pensions) it is possible that the
same person receives more than one pension. This bias should not, however, be large and
should not affect the evolution over time. In some countries, the number of contributors is
also an approximation based on the number of persons employed, due to the fact that, in
principle, every employed individual is under an obligation to pay a pension contribution to
social security schemes.
The following tables summarise the information received and allow for verifying the
credibility of the projections, for instance, the relationship between the projected numbers of
pensioners and the population over the age of 65. Also, the pension system dependency ratio
between the numbers of pensioners and contributors and the inverse ratio, the support ratio,
between the numbers of contributors and pensioners, are important indicators as regards the
sustainability of the pension systems.
Table 3-19 Number of pensioners in public pension schemes
Public pensions, number of pensioners
Country
2004
2010
2015
2020
2025
2030
2040
Change
2004-2030
2050
Change
2030-2050
Change
2004-2050
BE
2501
2635
2870
3144
3456
3748
4052
4050
1247
302
CZ
2629
2795
2893
2984
3099
3215
3483
3496
586
281
1549
867
DK
1255
1395
1511
1598
1675
1749
1787
1702
494
-47
446
DE
23840
25684
26829
28256
30066
32082
33792
34441
8242
2360
10601
EE
378
369
357
352
356
359
365
377
-19
18
-1
GR
ES
8519
9088
9676
10392
11389
12623
14715
15059
4104
2436
6540
FR
IE 2)
12925
13815
15023
16288
17417
18484
19948
19931
5559
1447
7006
606
721
814
916
1033
1162
1416
1674
556
512
1068
IT
15595
15665
16088
16783
17777
19131
20774
20206
3535
1076
4611
205
CY
89
113
138
166
194
218
243
293
129
76
LV
599
533
529
544
567
575
588
611
-24
36
12
LT
1248
1292
1295
1314
1335
1357
1388
1402
108
46
154
LU
128
142
158
178
204
235
293
335
107
100
207
HU
3069
3210
3262
3343
3353
3353
3529
3467
284
114
398
MT
60
74
86
97
107
113
122
130
53
16
69
NL
3317
3437
3818
4156
4514
4879
5291
5120
1562
241
1803
AT
2337
2449
2525
2611
2777
2912
3023
2892
575
-20
555
PL
7652
7254
7445
7975
8392
8635
9139
9574
983
940
1922
PT
3048
3304
3585
4005
4351
4698
5244
5454
1649
757
2406
SI
524
571
609
647
686
722
778
781
198
59
257
SK
1212
1282
1347
1458
1570
1664
1833
1919
452
255
707
FI
1282
1413
1530
1640
1721
1771
1748
1714
488
-57
432
SE
2126
2275
2507
2715
2902
3079
3297
3327
953
248
1201
8401
UK
1)
EU15
77481
79093
79892
80731
81347
82023
83703
85882
4542
3859
EU10
EU12 1)
17460
17572
17560
17545
17521
17491
17578
17816
31
325
356
74100
75630
76388
77177
77737
78354
79889
81928
4254
3574
7828
1)
94941
96665
97453
98276
98869
99515
101281
103698
4574
4184
8757
EU25
1) excluding countries which have not provided data
2) IE: only the number of pensioners in the social security scheme
96
Table 3-20 Number of pensioners receiving public pensions relative to the population
aged 65 and over
Public pensions, number of pensioners / 100 persons aged 65+
Country
2004
2010
2015
2020
2025
2030
2040
Change 2004-Change 2030-Change 20042030
2050
2050
2050
BE
140
143
142
142
141
139
136
137
-2
-2
-4
CZ
185
178
159
145
141
141
140
127
-44
-14
-58
DK
156
156
148
144
140
136
127
124
-20
-12
-32
DE
160
152
155
153
151
146
141
148
-14
2
-12
EE
173
-33
-10
-43
GR
166
:
159
:
151
:
146
:
140
:
136
:
130
:
:
ES
119
118
116
116
115
114
108
100
-5
-14
-19
FR
IE 2)
132
134
129
125
122
119
115
115
-13
-4
-17
135
142
135
131
127
125
120
117
-10
-8
-18
IT
140
130
125
124
124
123
115
111
-18
-12
-29
CY
102
107
109
112
113
113
111
115
10
2
13
LV
160
137
138
140
139
134
129
125
-26
-9
-34
-59
LT
241
239
238
235
222
205
190
182
-36
-23
LU
201
205
206
208
209
209
215
235
8
26
34
HU
196
192
184
170
159
158
154
138
-38
-20
-57
MT
116
123
113
110
108
106
109
103
-10
-3
-12
NL
147
138
131
128
125
122
118
119
-26
-2
-28
AT
185
167
161
155
148
137
123
117
-48
-20
-68
PL
155
142
130
118
108
105
104
97
-50
-8
-58
PT
173
175
176
182
183
180
175
169
7
-11
-4
SI
175
172
170
157
149
144
139
132
-31
-12
-43
SK
195
195
185
169
159
154
152
138
-41
-16
-57
FI
158
158
142
134
129
125
122
122
-33
-3
-36
SE
138
136
133
134
135
135
134
135
-3
0
-3
UK
EU15 1)
:
:
:
:
:
:
:
:
144
140
137
135
133
130
125
124
-14
-7
-21
EU10
EU12 1)
173
164
153
140
131
127
126
116
-45
-12
-57
144
140
137
135
133
130
124
123
-14
-7
-21
EU25 1)
149
144
140
136
133
130
125
122
-19
-8
-27
1) excluding countries which have not provided data
2) IE: only the number of pensioners in the social security scheme
As expected, the number of pensioners is greater than the number of persons aged 65 or more
because the number of pensioners also includes persons who receive early, disability and
survivors’ pensions. Also, in many countries, the statutory old-age retirement age is below 65.
Furthermore, in principle, the number of pensioners also includes those pensioners who
receive their pensions abroad but are not included in the resident population. In this respect,
the quality of data may differ across countries and this aspect is better reflected in some
countries’ figures (e.g. Sweden) than for some others. The comparison between these figures
shows, however, by how much the numbers of pensioners exceed the old-age population and
provides some help in assessing whether the projected trend in the numbers of pensioners is
feasible. All countries expect a decreasing trend in the relationship between the number of
pensioners and the old-age population. It is also expected to remain well above 1, except in
Spain, Malta and Poland where it will be close to 149.
Table 3-21 compares the numbers of pensioners and contributors in the public pension
scheme for those countries that have provided data for both of these variables, while Table
3-22 presents the numbers of contributors. In principle, the number of contributors includes
those who pay a specific pension (or social security) contribution, calculated at the end of the
year, in order to avoid double counting due to short-term work contracts. The figures largely
reflect the demographic old-age dependency ratios, but provide a more focused insight into
49
In Luxembourg, the relationship is not very meaningful because the number of pensioners is largely
driven by the number of cross-border workers becoming eligible to pensions.
97
the projected numbers of pension recipients and contributors. In general, the pension system
dependency ratio is much higher than that drawn from the population figures alone due to the
fact that persons aged 65 and more are virtually all pensioners while the number of
contributors constitutes only a part of the working-age population. In many countries, the
pension system dependency ratio is double the demographic old-age dependency ratio (BE,
DE, LT, SI, SK). In contrast, the pension system dependency ratio is close to the demographic
dependency ratio in Ireland (concerning social security pensions only) and the Netherlands.
Table 3-21 Pension system dependency ratio: number of pensioners relative to the
number of contributors in public pension schemes
Public pensions, number of pensioners / 100 contributors
Country
2004
2010
2015
2020
2025
2030
2040
2050
Change
2004-2050
Change
2030-2050
Change
2004-2050
BE
59
59
62
68
76
84
93
95
25
11
36
CZ
55
57
59
62
67
71
86
97
16
25
41
DE
74
75
75
80
88
98
109
117
24
19
43
EE
63
59
57
59
62
64
68
77
1
13
14
52
54
57
62
66
71
77
78
18
8
26
23
24
26
28
30
33
40
49
10
16
26
DK
GR
ES
FR
IE 2)
IT
68
65
65
68
73
82
97
99
13
18
31
CY
26
28
32
37
42
47
52
64
22
17
38
LV
55
45
45
49
54
57
61
70
2
13
15
LT
92
90
88
93
100
106
114
126
13
20
34
LU
42
41
44
47
51
56
61
62
14
6
20
HU
76
76
78
81
83
85
97
103
9
19
27
MT
38
43
48
54
58
59
61
63
22
4
25
NL
27
28
30
32
34
36
39
38
8
2
10
AT
66
64
65
67
74
80
86
86
13
6
20
PL
53
45
44
46
49
51
59
71
-2
19
18
PT
71
74
82
92
102
114
140
157
43
43
86
SI
65
65
69
75
82
90
105
113
25
24
49
SK
54
53
53
57
61
67
83
101
13
34
47
FI
55
60
65
70
75
78
78
78
22
0
23
38
SE
UK
1)
EU15
71
71
73
78
85
93
105
109
22
16
EU10
EU12 1)
59
54
54
57
60
63
73
84
4
21
25
68
68
70
75
81
89
101
104
21
15
36
1)
68
67
69
74
79
87
98
104
18
18
36
EU25
1) excluding countries which have not provided information
2) IE: only the number of pensioners and contributors in the social security scheme
98
Table 3-22 Number of contributors to public pension schemes
Public pensions, number of contributors
Country
2004
2010
2015
2020
2025
2030
2040
Change
2004-2030
2050
Change
2030-2050
Change
2004-2050
BE
4249
4491
4623
4620
4545
4457
4355
4281
208
-176
32
CZ
4767
4880
4911
4776
4650
4500
4056
3620
-267
-881
-1147
DE
32206
34316
35624
35263
34135
32698
30869
29472
492
-3226
-2734
EE
599
626
624
600
578
563
538
492
-37
-70
-107
FR
IE 2)
24645
25796
26342
26229
26224
26194
25835
25527
1549
-667
882
2661
3003
3175
3317
3445
3541
3557
3437
880
-104
776
IT
22777
24247
24755
24775
24323
23378
21440
20340
601
-3038
-2437
DK
GR
ES
CY
344
404
438
454
458
459
469
456
115
-3
112
LV
1089
1183
1167
1111
1053
1013
963
872
-76
-141
-217
-237
LT
1350
1442
1464
1416
1339
1284
1216
1112
-66
-171
LU
307
344
364
378
398
421
477
541
115
119
234
HU
4026
4206
4201
4137
4057
3956
3629
3351
-70
-605
-675
MT
159
171
177
181
185
191
199
205
32
14
45
NL
12064
12484
12844
13156
13454
13612
13660
13615
1548
3
1551
AT
3526
3799
3864
3870
3764
3653
3500
3370
127
-283
-156
PL
14433
16156
16988
17287
17227
16815
15443
13565
2382
-3250
-868
PT
4285
4436
4362
4335
4268
4108
3751
3468
-177
-640
-817
SI
807
873
878
860
833
803
741
688
-4
-115
-119
SK
2244
2419
2550
2579
2568
2483
2213
1901
239
-582
-343
FI
2311
2365
2360
2341
2305
2272
2246
2187
-38
-85
-123
109031
-2793
SE
UK
EU15 1)
115281
118313
118284
116859
114335
109692
106238
5304
-8097
EU10
EU12 1)
29819
32360
33399
33401
32948
32067
29466
26262
2248
-5805
-3557
109031
115281
118313
118284
116859
114335
109692
106238
5304
-8097
-2793
EU25 1)
138850
147641
151712
151685
149807
146402
139158
132501
7552
-13902
-6349
1) excluding countries which have not provided data
2) IE: only the number of contributors to the social security scheme
Table 3-23 compares the projected evolution between the numbers of contributors and
pensioners, showing how many contributors relative to each pensioner there will be. This is
known as the support ratio. As the ageing of the population will increase the numbers of
pensioners and the numbers of the persons employed are projected to decrease, the support
ratio will decline.
Currently, in most countries there are between 1.5 and 2.0 contributors for each pensioner;
with the highest numbers of contributors in Ireland (4.4), Cyprus (3.9), the Netherlands (3.6),
Malta (2.6) and Luxembourg (2.4) and the lowest numbers in Lithuania (1.1), Germany and
Portugal (1.4). By 2050, the support ratio is projected to come close to 1 in most countries; in
some countries (DE, PT, LT and SI) even significantly below 1 while remaining above 1.5
only in the Netherlands (2.7), Ireland (2.0), Luxembourg, Cyprus and Malta (1.6).
99
Table 3-23 Support ratio: Number of contributors relative to the number of pensioners
in public pension schemes
Public pensions, number of contributors / 100 pensioners
Country
2004
2010
2015
2020
2025
2030
2040
2050
Change 2004-Change 2030-Change 20042030
2050
2050
BE
170
170
161
147
132
119
107
106
-51
-13
-64
CZ
181
175
170
160
150
140
116
104
-41
-36
-78
DE
135
134
133
125
114
102
91
86
-33
-16
-50
EE
159
170
175
171
162
157
147
130
-2
-26
-28
191
187
175
161
151
142
130
128
-49
-14
-63
439
416
390
362
333
305
251
205
-134
-99
-234
DK
GR
ES
FR
IE 2)
IT
146
155
154
148
137
122
103
101
-24
-22
-45
CY
387
359
317
273
235
211
193
156
-176
-55
-232
LV
182
222
220
204
186
176
164
143
-6
-33
-39
LT
108
112
113
108
100
95
88
79
-13
-15
-29
LU
240
242
230
212
195
179
163
162
-60
-18
-78
HU
131
131
129
124
121
118
103
97
-13
-21
-35
-106
MT
264
233
206
186
173
168
163
158
-95
-11
NL
364
363
336
317
298
279
258
266
-85
-13
-98
AT
151
155
153
148
136
125
116
117
-25
-9
-34
PL
189
223
228
217
205
195
169
142
6
-53
-47
PT
141
134
122
108
98
87
72
64
-53
-24
-77
-66
SI
154
153
144
133
121
111
95
88
-43
-23
SK
185
189
189
177
164
149
121
99
-36
-50
-86
FI
180
167
154
143
134
128
128
128
-52
-1
-53
166
-55
SE
UK
EU15 1)
166
162
152
140
128
115
111
-38
-17
EU10
EU12 1)
171
185
186
177
168
159
137
119
-12
-40
-52
166
166
162
152
140
128
115
111
-38
-17
-55
EU25 1)
167
170
166
157
145
134
119
112
-33
-22
-55
1) excluding countries which have not provided data
2) IE: only the numbers of contributors to and pensioners from the social security scheme
3.3.5.
Pension contributions and assets of pension funds
The projections of contributions to pension schemes were made under the assumption of a
constant contribution rate unless there are clear decisions on changes in the contribution
policy. The contributions to social security or occupational and private pension schemes
include only specific contributions to pension schemes paid by the employers and employees
as well as the self-employed. In the case of Luxembourg and Malta, it is stipulated that also
the state pays a contribution to the social security pension scheme. This contribution is equal
to the contributions paid by the employer and the employee, thus amounting to one third of
the total contribution revenues. In the Luxembourg projections, the state contribution is also
included in the contributions. In general, however, state subsidies are not included in the
contributions but the difference between the pension expenditure and pension contributions
shows what part of the expenditure needs to be financed from other sources, in general from
government tax revenues. Some countries (BE, ES) have only a general contribution rate for
all social insurance expenditure and they were not able to provide a separate estimate of the
pension contribution while for Portugal and Malta decided to present the total amount of the
general social security contribution. Moreover, in Denmark, social security pensions are
financed virtually entirely by taxes and no contributions are shown.
Table 3-24 shows the projection for pension contributions to social security pension schemes
as a share of GDP. As the contribution revenues are driven by wage growth, their share of
GDP would remain relatively constant. However, there are a number of reasons why the share
100
of contributions changes over time. In Germany, the share of contributions relative to GDP
will grow because it is already in the legislation that the contribution rate has to be raised
(however, not higher than 22% of wages) in order to cover the constant ratio of expenditure.
Also in France, an increase in the contribution rate will materialise already in 2006. In
contrast, in Malta, the ceiling of the contribution base is indexed to prices, which results in a
decreasing trend in contribution revenues as a share of GDP. Moreover, a decreasing trend in
contribution revenues is observed in those new Member States which have switched a part of
the social security scheme into a private scheme and where an increasing number of people
are joining the private scheme or the switched part is still growing. Consequently, an
increasing share of the total contribution will be directed to the private scheme in EE, LV, LT,
HU and SK.
Table 3-24 Pension contributions to public pension schemes as a share of GDP
Public pensions, contributions as % of GDP
Country
2004
2010
2015
2020
2025
2030
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
8,9
8,9
8,9
8,9
8,9
8,9
8,9
8,9
0,0
0,0
0,0
BE
CZ
DK
DE
7,7
7,3
6,9
7,3
7,8
8,3
8,7
8,9
0,6
0,6
1,2
EE
6,5
6,6
6,5
6,4
6,3
6,2
6,1
6,1
-0,3
-0,1
-0,4
FR
12,8
12,9
12,9
12,9
12,9
12,9
12,9
12,9
0,0
0,0
0,0
IE
3,6
3,4
3,4
3,4
3,4
3,4
3,4
3,4
-0,3
0,0
-0,3
0,4
GR
ES
IT
10,2
10,3
10,4
10,4
10,4
10,3
10,5
10,6
0,1
0,3
CY
5,5
6,4
6,9
7,2
7,2
7,2
7,4
7,1
1,7
-0,1
1,6
LV
7,1
6,1
5,7
5,6
5,5
5,4
5,4
5,4
-1,6
0,0
-1,7
-0,6
LT
6,8
6,3
6,2
6,1
5,9
6,0
6,1
6,1
-0,8
0,2
LU
9,9
10,0
10,1
10,1
10,1
10,0
10,0
10,0
0,1
0,0
0,2
HU
MT 2)
7,7
6,8
6,6
6,6
6,5
6,6
6,7
6,8
-1,1
0,2
-1,0
7,1
6,8
6,4
5,9
5,4
4,8
3,9
3,3
-2,3
-1,4
-3,8
NL
6,8
6,4
6,4
6,4
6,4
6,5
6,7
6,6
-0,3
0,1
-0,2
AT
9,0
9,1
9,0
8,9
8,7
8,6
8,5
8,6
-0,3
-0,1
-0,4
PL
PT 2)
7,7
8,0
8,1
8,1
8,0
7,9
7,9
7,9
0,3
0,0
0,3
10,5
10,5
9,9
9,6
9,5
9,4
9,1
9,2
-1,1
-0,1
-1,2
SI
9,3
10,1
10,4
10,6
10,7
10,7
10,6
10,6
1,4
-0,1
1,3
SK
6,5
5,0
4,9
4,8
4,7
4,7
4,7
4,4
-1,8
-0,3
-2,0
FI
9,1
9,0
9,7
10,3
10,8
11,2
11,2
11,2
2,0
0,1
2,1
SE
7,7
7,5
7,4
7,4
7,4
7,4
7,3
7,3
-0,3
-0,1
-0,4
UK
1)
EU15
5,7
5,9
6,1
6,2
6,2
6,3
6,3
6,3
0,6
0,0
0,5
8,7
8,6
8,5
8,6
8,8
8,9
9,0
9,0
0,2
0,2
0,3
EU10
EU12 1)
7,8
7,6
7,6
7,6
7,5
7,5
7,5
7,5
-0,2
0,0
-0,3
9,6
9,4
9,3
9,4
9,6
9,7
9,9
10,0
0,2
0,3
0,5
1)
8,7
8,5
8,5
8,5
8,7
8,8
8,9
8,9
0,1
0,2
0,3
EU25
1) excluding countries which have not provided data
2) MT and PT: including the total social security contribution
Table 3-25 shows the projections for the extent to which the contributions alone can finance
the future public pension expenditure and how the additional financing needs will develop
under current policies, concerning both pensions and their contributions. It can be seen that
additional financing need will grow markedly in most countries. However, it should be noted
that public pensions already include in the starting position pensions which are by their very
nature solidarity pensions or aimed at preventing poverty in the old age (such as minimum
guarantee pensions in all countries and also disability pensions in countries with definedcontribution pension schemes) and, thus, financed by general tax revenues. Moreover, in
some countries, disability pensions (benefits) are under the sickness insurance scheme; in
these cases (FR and SE) the contribution paid to sickness insurance schemes is not included in
these projections.
101
The results show that only in a few countries (CZ, EE, FR, LV, LT and LU) are public
pensions more or less entirely financed by dedicated contributions50, while in a number of
countries a significant share of pensions is financed from general tax revenues (or other social
insurance contributions); almost one third of the expenditure in Germany, Italy, Austria and
Sweden; over 40% of the expenditure in Poland. Towards the end of the projection period, the
additional financing needs are projected to grow to about one third also in CZ and LT, and
even greater in IE, HU, LU, MT, NL, PT, SI and SK while the financing situation in Poland is
projected to be balanced. On average in the EU, the contribution financing of public pensions
would drop from about 80% to 72% between 2004 and 2050.
Table 3-25 Social security pension contributions relative to public pensions
Public pensions, contributions / gross pensions
Change
Change
2004-2030 2030-2050
Change
2004
2010
2015
2020
2025
2030
2040
2050
105
108
109
105
100
93
73
63
DE
68
69
66
67
68
68
68
68
0
0
0
EE
98
97
109
119
125
132
139
146
33
14
47
FR
100
99
98
94
92
90
86
87
-10
-3
-13
IE
76
65
57
52
46
43
36
30
-34
-12
-46
IT
72
74
75
74
72
68
66
72
-3
4
1
CY
80
80
79
73
67
59
49
36
-21
-23
-44
LV
104
124
125
115
104
97
91
97
-7
1
-7
LT
101
96
94
87
78
75
75
72
-25
-4
-29
Country
2004-2050
BE
CZ
-12
-30
-42
DK
GR
ES
LU
99
102
93
85
74
67
59
58
-32
-9
-41
HU
MT 2)
74
61
57
52
50
49
42
40
-25
-9
-35
96
77
66
58
53
52
50
47
-43
-5
-48
NL
88
84
77
71
66
61
57
59
-27
-2
-29
AT
67
71
71
69
65
62
64
70
-5
8
3
PL
PT 2)
55
71
83
83
84
87
92
99
31
13
44
95
88
78
68
64
59
49
44
-36
-14
-50
SI
85
91
90
86
80
74
63
58
-10
-16
-27
SK
90
75
75
69
64
61
56
49
-29
-12
-41
FI
85
81
81
80
80
80
81
82
-6
2
-4
SE
72
74
72
71
70
67
63
65
-6
-2
-8
UK
1)
EU15
87
90
91
90
86
80
76
73
-7
-7
-14
80
82
80
79
77
74
71
72
-6
-2
-8
EU10
EU12 1)
72
78
83
80
78
77
71
67
5
-9
-4
80
81
79
77
75
73
71
72
-7
-1
-7
1)
80
81
80
79
77
74
71
72
-6
-2
-8
EU25
1) excluding countries which have not provided data
2) MT and PT: including the total social security contribution
One way of meeting the additional financing needs is to accumulate reserve funds for social
security pension schemes. A statutory partial funding is required in the social security pension
schemes in Finland, Luxembourg and Sweden. Furthermore, many more countries have
established reserve funds which may be accumulated by surpluses in the social security funds
or in central government budgets or by other commitments taken by the government (notably
Ireland). Such reserve funds51 dedicated to the financing of future increased pension
50
The figures for Malta and Portugal include also contributions for benefits other than pensions.
51
The term ‘reserve funds’ is used to cover also other reserves dedicated for the financing of future
pensions, such as accumulated reserves of state pension special budget in Latvia, which do not
constitute a fund in its proper meaning.
102
expenditure exist currently in BE, CZ, CY, DE, EE, FR, IE, LV, PL and PT. However, the
magnitude of these reserve funds is essentially smaller than that of the statutory pension funds
in LU, FI and SE.
The projection of the assets is based on the projected flows of contributions coming into the
fund and pensions paid out of the fund. An annual real rate of return of 3% over the whole
projection period is assumed. The figures shown for Sweden also include the funds of private
pension funds for the part which concerns the statutory part of the social security scheme. For
Ireland, the figures of assets presented cover both Social Security and Public Services
occupational pensions.
The projections show that most of the reserve funds will be exhausted before the end of the
projection period (except in EE and IE in particular). In Portugal, the fund will be exhausted
already by 2015 and, thereafter, a continuously increasing gap will emerge. It is projected to
reach 35% of GDP in 2030 and 173% of GDP in 2050. Also the statutory fund in the
Luxembourg pension scheme will be exhausted by 2035 under current contribution and
accumulation policies and the debt of the pension system would reach 34% of GDP in 2040
and 100% in 2050. In Cyprus, the financing gap in 2050 is projected to rise 45% of GDP. In
contrast, it is projected that the Finnish and Swedish (up to 2040) pension funds will grow in
size. It should be noted that the funds may not be used for all of the financing needs of public
pensions. In particular, the statutory funds in Luxembourg are only for the earnings-related
pension scheme of the private sector, in Finland for the earnings-related pension schemes of
all sectors and the Swedish fund is only for the old-age insurance pensions.
Table 3-26 Assets in public pension schemes as a share of GDP
Public pensions, assets as % of GDP
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
12,0
27,2
39,2
:
:
:
Country
2004
2010
2015
2020
2025
2030
BE
4,4
7,3
13,4
16,4
13,6
1,9
-2,5
CZ
0,3
3,5
6,8
9,9
11,0
9,4
9,1
DE
0,1
0,4
0,8
EE
1,0
2,6
7,5
13,0
25,6
40,2
GR
:
:
:
:
:
:
:
:
ES
1)
FR
1,2
2,0
2,9
4,0
3,5
2,8
1,5
0,0
1,6
-2,8
-1,2
IE
7,3
11,1
14,4
18,1
22,5
26,0
28,3
21,9
18,7
-4,1
14,6
CY
39,3
39,6
39,7
37,9
33,4
25,1
1,9
-14,2
LV
-0,3
5,2
7,8
9,3
8,7
6,5
0,2
6,8
23,6
31,7
37,4
39,2
32,9
17,8
0,4
0,3
0,3
0,4
0,2
0,4
DK
IT
LT
LU
-5,8
HU
MT
NL
AT
PL
0,1
0,4
PT
4,3
4,0
0,4
0,5
0,3
SI
SK
FI
52,4
59,3
63,1
66,0
68,2
69,9
71,3
72,9
17,5
2,9
20,5
SE
32,1
40,0
43,1
45,6
47,7
49,6
47,7
44,4
17,4
-5,2
12,2
UK
1) France: only the assets of the Fonds de Réserves des Retraites, not those of specific pension schemes
103
Table 3-27 presents the projections for the assets in all pension funds, including funds in
social security schemes and also the occupational and private funds. These funds are covered
in the projections corresponding to the coverage of occupational and private statutory
pensions presented in Table 3-16.
Table 3-27 Assets in all pension schemes as a share of GDP
All pensions, assets as % of GDP
2040
2050
Change
2004-2030
Change
2030-2050
Change
2004-2050
47,7
50,5
98,2
1,6
-2,8
-1,2
57,1
14,1
71,1
27,6
24,8
52,4
46,0
23,7
69,7
:
:
:
13,6
108,1
Country
2004
2010
2015
2020
2025
2030
BE
4,4
7,3
13,4
16,4
13,6
1,9
-2,5
CZ
0,3
3,5
6,8
9,9
11,0
9,4
9,1
DE
0,1
0,4
0,8
EE
2,8
9,4
15,9
25,3
37,6
50,5
76,9
101,0
1,2
2,0
2,9
4,0
3,5
2,8
1,5
0,0
CY
39,3
39,6
39,7
37,9
33,4
25,1
1,9
LV
0,3
12,9
25,9
38,0
48,2
57,4
68,8
71,5
LT
0,3
4,3
8,6
14,0
20,7
27,9
41,5
52,7
LU
23,6
31,7
37,4
39,2
32,9
17,8
HU
4,0
13,2
21,9
31,5
41,1
50,0
DK
GR
ES
FR
IE
IT
-14,2
-5,8
67,7
73,7
MT
NL
135,5
160,6
177,5
195,6
214,5
230,1
241,0
243,7
94,6
:
:
:
PL
7,1
15,9
24,0
33,5
42,5
51,1
69,9
85,0
44,0
34,0
78,0
PT
4,3
4,0
SI
1,4
5,5
9,6
13,9
18,3
22,6
30,1
35,9
21,3
13,3
34,5
7,0
12,8
18,9
25,1
31,5
45,7
58,0
31,5
26,5
58,0
AT
SK
FI
52,4
59,3
63,1
66,0
68,2
69,9
71,3
72,9
17,5
2,9
20,5
SE
38,6
53,5
60,7
66,0
69,7
72,3
68,1
60,9
33,7
-11,4
22,3
UK
3.4.
Sensitivity analyses
A number of sensitivity analyses were carried out in the projections with the aim of providing
some insight into the question of how sensitive the projections are to different assumptions
and projected population and labour force developments, which inherently bring a major
degree of uncertainty to long-run expenditure projections.
The sensitivity scenarios were all run in relation to the baseline scenario, changing only one
parameter in each sensitivity scenario from that in the baseline scenario. The following
sensitivity tests were run:
•
Higher life expectancy scenario assumes an increase in life expectancy, which
corresponds roughly to an increase in life expectancy at birth of 1-1.5 years by 2050.
Specifically, it was introduced by decreasing the age-specific mortality rates by 15%
linearly over the period 2004-2050.
•
Higher employment rate scenario assumes that the employment rate will increase by
1 p.p. over the period 2005-2015 and thereafter will remain at a 1 p.p. higher level in
the period 2015-2050 compared with the baseline projection. The higher employment
rate was assumed to be achieved by lowering the rate of structural unemployment (i.e.
the NAIRU).
104
•
Higher employment rate of older workers scenario assumes that the employment rate
of older workers will increase by 5 p.p. over 2005-2015 and thereafter will remain at a
5 p.p. higher level over the period 2015-2050, compared with the baseline projection.
The higher employment rate is assumed to be achieved through a reduction in the
inactive population.
•
Higher and lower labour productivity scenarios assumes an increase/decrease in the
labour productivity growth rate by 0.25 p.p. over 2005-2015 and thereafter remaining
at the 0.25 p.p. higher/lower level in comparison with the labour productivity growth
rate in the baseline projection.
•
Higher and lower interest rate scenarios assume interest rates of 4 and 2% vs. 3% in
the baseline scenario.
Table 3-28 and Table 3-29 provide an indication of the sensitivity of the pension expenditure
projections to various assumptions while Table 3-30 looks at the sensitivity of the projections
of the total assets of pension funds and Table 3-31 at the sensitivity of the projections of the
ratio between contributions and pensions in public schemes. Although the assumed magnitude
of the changes in different sensitivity scenarios is not easily comparable, it could be
interpreted that the public pension expenditure projections are most sensitive to the
assumption of life expectancy and the assumption of labour productivity growth rate, while
the assumptions of the interest rate and of higher employment rates have only a small impact
on the results.
The magnitude of the impact of different assumptions on pension spending depends critically
on the pension system design: how responsive the system is to changes in economic and
demographic developments.
A higher life expectancy should have a larger impact on pension spending in a defined-benefit
scheme where the initial level of the pension does not depend on the time being spent in
retirement. In contrast, a defined-contribution scheme fully accommodates with the time
being spent in retirement as the accumulated pension capital will be converted into annuities
at the time of retirement and this calculation takes into account life expectancy.
Higher and lower labour productivity assumptions affect pension spending through their link
to the increase in wages. Usually in the projections, it is assumed that real wages increase in
line with labour productivity growth rates. The impact on pension spending depends directly
on the extent to which pensions are indexed to wage increases. If pensions are indexed to
wages, the share of pension spending relative to GDP should remain unchanged under
different assumptions about the labour productivity growth rates, since the labour productivity
growth rate determines wage growth. In contrast, if pensions are indexed to prices only (or to
a hybrid index of wages and prices) and the real wage growth rate is positive, the share of
pension spending relative to GDP will decrease.
Higher and lower interest rates have no impact on pension spending (relative to GDP) as far
as fully pay-as-you-go pension systems are concerned. Only in funded schemes does the
interest rate assumption matter. A higher interest rate (thus also a higher return on pension
assets) helps the financing of the pension scheme and results in a higher accumulation of
pension funds if it concerns a defined-contribution scheme. In this case, the contribution rate
remains unchanged but asset accumulation increases, also allowing higher pensions to be
paid, thereby resulting in higher pension spending. In contrast, in a funded defined-benefit
105
scheme (such as there are in the Netherlands in particular), the pension expenditure would not
be affected but higher interest (return) rates would allow lower contributions, which in turn
would result in a lower accumulation of pension assets as well.
The impact of higher employment rates (whether overall employment rates or employment
rates of older workers) on pension spending depends critically on what is assumed of how the
gain in higher employment rates is achieved and how the pension system design responds to
such changes. If a gain in higher employment rates is achieved through decreased
unemployment rates, it usually also increases the accrual of pension rights of the person
moving from unemployment to employment, thereby increasing the level of his pension and
the overall spending on pensions. However, the higher employment rate also results in higher
GDP and, consequently, the ratio between pension spending and GDP would not be affected
much. Also the effect on the ratio between contributions and pensions remains largely
unchanged provided that there is a close link between the contributions and the pension rights.
Similarly, when considering the change in the employment rate of older workers, the impact
depends essentially on whether it increases the person’s pension rights or not. Only in the case
of a defined-benefit pension system and if the higher employment rate of older workers was
gained through a reduction of non-actuarial early pensions, would the decrease in pension
spending relative to GDP be notable. Nevertheless, higher employment rates result in welfare
gains both at the individual level, allowing higher earnings when still employed and higher
pensions when retired, and for society, resulting in higher GDP and higher income per capita.
Detailed projection results for each sensitivity test are presented in Annex (Tables 3-1 – 328). The results of the sensitivity scenarios can be summarised as follows:
•
Higher life expectancy is projected to increase public and total pension expenditure
by 0.3 percentage points on the average in the EU. The largest projected impacts on
public pension expenditure are in DK, FR, PT and SI (by 0.6 p.p. of GDP) and in BE,
MT, NL and SK by 0.5 p.p. As expected, the projected impact is smaller in countries
with defined-contribution schemes (IT, LV, PL and SE).
•
Higher employment rate and higher employment rate of older workers are projected
to result in only small and rather similar changes in pension spending. In most
countries, the level of public or total pension spending as a share of GDP will remain
unchanged; only in Hungary and Slovenia, notable decreases (0.4-1.1 p.p.) are
projected and smaller decreases (0.3-0.4 p.p.) in BE, CZ, LT, AT). A higher
employment rate of older workers appears to have a somewhat stronger impact in DK,
EE and FR than a general increase in employment. In contrast, the German
sustainability factor is designed in such a way that pension spending responses to
changes in employment and to the change in ratio between the numbers of employed
and pensioners. Some countries also project a small increase in pension spending,
which is a feasible result in a defined-contribution scheme in particular because the
persons in employment will accrue more pension rights. It can also be seen that the
ratio between contributions and benefits is robust for changes in employment due to
the fact that such changes affect both the contribution and the benefit side as well as
the level of GDP.
•
Higher and lower labour productivity result in relatively symmetric
decreases/increases in the level of pension spending, on average by 0.3-0.4 percentage
points of GDP. The changes are highest (0.7-1.0 p.p.) in ES, CY, MT, AT and PT,
106
while in DK, DE, IE, LU, NL and SI pensions are projected to rise in line with
earnings and (virtually) no change is projected.
•
Higher and lower interest rates have no impact on the level of public pension
expenditure in most countries. Only in Sweden, does it have a noticeable impact:
higher interest rates are projected to increase pension spending by 0.3 p.p. and lower
interest rates to decrease spending by 0.3 p.p. This impact is due to the definedcontribution funded public scheme. However, the interest rate plays a more important
role in countries with funded occupational and private statutory schemes. A more
noticeable impact is seen for total pension expenditure as well as for total assets in
pension funds. Due to the funded schemes, the total pension spending could
increase/decrease by 0.5-1.1 percentage points in EE, LV, LT, HU, SK and SE. The
impact of higher/lower interest rates on the increase/decrease in total pension assets is
projected to be in the range of 10-17 percentage points in countries with private
statutory schemes, while in the Netherlands (which has large occupational funds), the
impact could be about 30-40 percentage points of GDP.
Table 3-28 Summary of the changes in gross public pension expenditure increases as a
share of GDP between 2004 and 2050 52
D iffe re n c e in p u b lic p e n s io n e x p e n d itu r e in c re a s e s a s p e rc e n ta g e p o in ts o f G D P
re la tiv e to th e b a s e lin e p ro je c tio n
B a s e lin e ,
change 20042050
H ig h e r life
e x p e c ta n c y
H ig h e r
e m p lo y m e n t
H ig h e r e m p l
H ig h e r la b o u r L o w e r la b o u r
o f o ld e r
p ro d u c tiv ity
p ro d u c tiv ity
w o rk e rs
H ig h e r
in te re s t ra te
Lower
in te re s t ra te
0 ,0
BE
5 ,1
0 ,5
-0 ,2
-0 ,3
-0 ,4
0 ,3
0 ,0
CZ
5 ,5
0 ,4
-0 ,2
-0 ,3
-0 ,3
0 ,2
0 ,0
0 ,0
DK
3 ,3
0 ,6
0 ,0
-0 ,3
0 ,0
0 ,0
0 ,0
0 ,0
DE
1 ,7
0 ,2
-0 ,1
0 ,0
0 ,0
0 ,0
0 ,0
0 ,0
EE
-2 ,5
0 ,1
0 ,0
-0 ,4
-0 ,2
0 ,2
0 ,0
0 ,0
ES
7 ,1
0 ,1
-0 ,1
-0 ,1
-0 ,9
1 ,0
0 ,0
0 ,0
FR
2 ,0
0 ,6
-0 ,1
-0 ,4
-0 ,4
0 ,5
0 ,0
0 ,0
IE
6 ,4
0 ,3
-0 ,1
-0 ,1
0 ,0
0 ,0
0 ,0
0 ,0
0 ,3
0 ,0
0 ,2
-0 ,5
0 ,6
0 ,0
0 ,0
-1 ,4
1 ,6
0 ,0
GR
IT
0 ,4
CY
1 2 ,9
LV
-1 ,2
0 ,2
0 ,0
0 ,0
-0 ,1
0 ,2
0 ,0
LT
1 ,8
0 ,4
-0 ,2
-0 ,3
-0 ,3
0 ,0
0 ,0
0 ,0
LU
7 ,4
-0 ,1
0 ,1
0 ,0
0 ,0
0 ,0
-0 ,1
HU
6 ,7
-0 ,3
-0 ,7
-1 ,1
-0 ,4
0 ,2
0 ,0
MT
-0 ,4
0 ,5
-0 ,1
0 ,0
-0 ,7
0 ,7
0 ,0
0 ,0
NL
3 ,5
0 ,5
-0 ,1
-0 ,1
-0 ,1
0 ,0
0 ,0
0 ,0
AT
-1 ,2
0 ,4
-0 ,2
-0 ,4
-0 ,8
1 ,0
0 ,0
0 ,0
PL
-5 ,9
0 ,2
-0 ,2
0 ,0
-0 ,4
0 ,2
0 ,0
0 ,0
PT
9 ,7
0 ,6
-0 ,2
-0 ,2
-1 ,2
1 ,3
0 ,0
0 ,0
SI
7 ,3
0 ,6
-0 ,4
-0 ,9
-0 ,1
-0 ,2
0 ,0
0 ,0
SK
1 ,8
0 ,5
0 ,0
0 ,1
-0 ,2
0 ,2
0 ,0
0 ,0
FI
3 ,1
0 ,2
0 ,0
-0 ,2
-0 ,4
0 ,5
0 ,1
-0 ,1
SE
0 ,6
0 ,3
-0 ,1
-0 ,2
0 ,3
0 ,3
-0 ,3
UK
E U 15
2 ,0
0 ,2
-0 ,1
-0 ,1
-0 ,4
0 ,3
0 ,0
0 ,0
1)
2 ,3
0 ,3
-0 ,1
-0 ,1
-0 ,3
0 ,4
0 ,0
0 ,0
E U 10
1)
0 ,3
-0 ,2
-0 ,3
-0 ,7
-0 ,4
0 ,2
0 ,0
0 ,0
E U 12
1)
2 ,6
0 ,3
-0 ,1
-0 ,2
-0 ,4
0 ,4
0 ,0
0 ,0
E U 25
1)
2 ,2
0 ,3
-0 ,1
-0 ,1
-0 ,3
0 ,4
0 ,0
0 ,0
1 ) e x c lu d in g c o u n trie s w h ic h h a v e n o t p ro v id e d d a ta
52
In the case of Luxembourg, where there is a large number of cross-border workers, it was agreed that the
sensitivity scenarios for higher life expectancy and higher employment rates are not easily interpretable and
comparable with other countries and that these scenarios were not be run for these reasons.
107
Table 3-29 Summary of the changes in all pension expenditure increases as a share of
GDP between 2004 and 2050
D iffe r e n c e in to ta l p e n s io n e x p e n d itu r e in c r e a s e s a s p e r c e n ta g e p o in ts o f G D P
r e la tiv e to th e b a s e lin e p r o je c tio n
B a s e lin e ,
change 20042050
H ig h e r lif e
e x p e c ta n c y
H ig h e r
e m p lo y m e n t
H ig h e r e m p l
o f o ld e r
w o rk e rs
BE
5 ,1
0 ,5
-0 ,2
-0 ,3
-0 ,4
CZ
5 ,5
0 ,4
-0 ,2
-0 ,3
-0 ,3
DE
1 ,7
0 ,2
-0 ,1
0 ,0
EE
-0 ,1
0 ,1
0 ,0
-0 ,4
ES
7 ,1
0 ,1
-0 ,1
-0 ,1
FR
2 ,0
0 ,6
-0 ,1
-0 ,4
0 ,3
0 ,0
0 ,2
H ig h e r la b o u r L o w e r la b o u r
p r o d u c t iv it y
p r o d u c tiv ity
H ig h e r
in te r e s t r a te
Lower
in te r e s t r a t e
0 ,3
0 ,0
0 ,0
0 ,2
0 ,0
0 ,0
0 ,0
0 ,0
0 ,0
0 ,0
-0 ,4
0 ,3
0 ,7
-0 ,5
-0 ,9
1 ,0
0 ,0
0 ,0
-0 ,4
0 ,5
0 ,0
0 ,0
-0 ,5
0 ,6
0 ,0
0 ,0
-1 ,4
1 ,6
DK
G R
IE
IT
0 ,4
CY
1 2 ,9
LV
1 ,5
0 ,2
0 ,0
-0 ,1
-0 ,3
0 ,3
0 ,8
-0 ,6
LT
3 ,7
0 ,4
-0 ,2
-0 ,4
-0 ,3
-0 ,1
0 ,5
-0 ,5
LU
7 ,4
-0 ,1
0 ,1
0 ,0
0 ,0
HU
9 ,9
-0 ,6
0 ,4
1 ,1
-0 ,8
M T
-0 ,1
-0 ,3
-0 ,8
-1 ,3
-0 ,4
0 ,5
-0 ,1
0 ,0
-0 ,7
0 ,7
0 ,0
0 ,0
NL
7 ,6
0 ,8
-0 ,1
0 ,0
-0 ,3
0 ,3
0 ,2
-0 ,3
AT
-1 ,2
0 ,4
-0 ,2
-0 ,4
-0 ,8
1 ,0
0 ,0
0 ,0
PL
-4 ,6
0 ,2
-0 ,2
0 ,0
-0 ,5
0 ,3
0 ,3
0 ,0
PT
9 ,7
0 ,6
-0 ,2
-0 ,2
-1 ,2
1 ,3
0 ,0
0 ,0
SI
8 ,3
-0 ,4
-1 ,4
-1 ,9
-1 ,1
-1 ,2
0 ,0
0 ,0
SK
4 ,1
0 ,4
0 ,0
0 ,0
-0 ,3
0 ,3
0 ,6
-0 ,5
-0 ,2
FI
3 ,1
0 ,2
0 ,0
SE
0 ,9
0 ,4
-0 ,1
UK
EU 15
-0 ,4
0 ,5
0 ,1
-0 ,1
-0 ,4
0 ,4
0 ,7
-0 ,6
1)
2 ,8
0 ,3
-0 ,1
-0 ,1
-0 ,4
0 ,4
0 ,1
-0 ,1
EU 10
1)
1 ,7
-0 ,2
-0 ,3
-0 ,7
-0 ,5
0 ,3
0 ,4
-0 ,2
EU 12
1)
2 ,8
0 ,3
-0 ,1
-0 ,2
-0 ,4
0 ,4
0 ,0
0 ,0
EU 25
1)
2 ,7
0 ,3
-0 ,1
-0 ,1
-0 ,4
0 ,4
0 ,1
-0 ,1
1 ) e x c lu d in g c o u n t r ie s w h ic h h a v e n o t p r o v id e d d a t a
Table 3-30 Summary of changes in total assets as a % of GDP between 2004 and 2050
D ifferen ce in total pen sion assets in creases as percentage po in ts of G D P relative
to th e b aselin e p rojection , 2004-2050 1)
B aseline,
B aseline,
H igher life
start level in change 2004expectancy
2004
2050
BE
4,4
CZ
0,3
H igher
em ploym ent
H igher em pl
Higher labour Lower labour
H igher
of older
productivity productivity interest rate
workers
Lower
interest rate
DK
DE
0,1
EE
2,8
98,2
1,2
-1,2
-0,2
4,5
1,6
1,3
-0,4
10,9
-8,8
0,0
0,0
0,0
0,0
0,0
0,0
GR
ES
FR
IE
IT
CY
39,3
LV
0,3
71,1
-1,3
0,3
-0,8
-0,1
0,9
12,1
-10,1
LT
0,3
52,4
1,5
0,1
-0,2
0,3
0,2
8,4
-7,1
LU
23,6
HU
4,0
69,7
-1,0
0,1
-0,6
-3,1
2,4
10,8
-9,1
135,5
108,1
13,7
1,1
0,7
-4,4
4,1
-32,4
40,7
PL
7,1
78,0
1,5
-0,5
0,0
-4,6
2,5
15,8
-12,6
PT
4,3
0,0
0,0
1,1
0,3
0,1
-2,2
2,6
9,3
-7,6
-1,2
MT
NL
AT
SI
1,4
34,5
SK
0,0
58,0
FI
52,4
20,5
-0,2
0,6
SE
38,6
22,3
-3,0
0,4
-4,4
4,3
16,0
-12,8
-1,7
2,8
17,2
-11,5
UK
1) D ifferences shown only for countries where the assets are projected to be positive in 2050 (excluding countries where
public reserves are projected to be exhausted before 2050, cf. tables 3-26 and 3-27)
108
Table 3-31 Summary of changes in the ratio between contributions and pension
expenditure in public schemes between 2004 and 2050
C h a n g e in th e r a tio b e tw e e n c o n tr ib u tio n s a n d p e n s io n e x p e n d itu r e 2 0 0 4 -2 0 5 0
B a s e lin e
2 0 0 4 , p u b lic
p e n s io n s
B a s e lin e
H ig h e r life
e x p e c ta n c y
H ig h e r
e m p lo y m e n t
105
-4 2
-4 4
-4 1
H ig h e r e m p l
H ig h e r la b o u r L o w e r la b o u r
o f o ld e r
p ro d u c tiv ity
p ro d u c tiv ity
w o rk e rs
H ig h e r
in te re s t ra te
Lower
in te re s t ra te
-4 2
-4 2
BE
CZ
-4 1
-4 1
-4 3
DK
DE
68
0
0
0
0
0
0
0
0
EE
98
47
44
44
41
50
37
47
47
GR
ES
FR
100
-1 3
-1 6
-1 2
-1 1
-1 0
-1 6
-1 3
-1 3
IE
76
-4 6
-4 7
-4 6
-4 6
-4 6
-4 6
-4 6
-4 6
IT
72
1
0
1
0
4
-2
1
1
CY
80
-4 4
-4 2
-4 7
-4 4
-4 4
LV
104
-7
-9
-6
-7
-4
-9
-7
-7
LT
101
-2 9
-2 9
-2 6
-2 5
-2 5
-2 7
-2 9
-2 9
LU
99
-4 1
-4 1
-4 1
-4 1
-4 1
HU
74
-3 5
-3 4
-3 3
-3 2
-3 4
-3 5
-3 4
-3 6
-4 5
MT
96
-4 8
-5 1
-4 7
-4 8
-4 8
-4 8
-4 8
-4 8
NL
88
-2 9
-3 1
-2 8
-2 8
-2 9
-2 9
-2 9
-2 9
AT
67
3
1
5
6
9
-2
3
3
PL
55
44
43
45
45
49
40
45
45
PT
95
-5 0
-5 1
-5 0
-5 0
-4 7
-5 2
-5 0
-5 0
SI
85
-2 7
-2 4
-2 5
-2 3
-2 7
-2 7
-2 7
-2 7
SK
90
-4 1
-4 3
-4 0
-4 1
-4 0
-4 2
-4 1
-4 1
-4
-3
-3
FI
85
-4
SE
72
-8
UK
EU15
-8
-2
-5
-1 0
2
-6
-9
-1 0
-6
-1 4
87
-1 4
-1 5
-1 3
-1 3
-1 1
-1 6
-1 4
1)
80
-8
-9
-8
-7
-6
-1 0
-8
-8
EU10
1)
72
-4
-2
-3
0
-2
-6
-3
-4
EU12
1)
80
-7
-8
-7
-6
-6
-9
-8
-7
EU25
1)
80
-8
-9
-7
-7
-6
-1 0
-8
-8
1 ) e x c lu d in g c o u n trie s w h ic h h a v e n o t p ro v id e d d a ta
109
4.
HEALTH CARE
4.1.
Introduction
A wider mandate covering demographic and non-demographic drivers of spending
The mandate from the ECOFIN Council to the EPC included a request to make projections
for public spending on health care53. This followed the 2001 projection exercise of the EPC
which examined the impact of demographic variables on health care spending.
The methodology used in 2001 was a pure ageing scenario which only considered the impact
of changes in the size and age-structure of the population on health care spending. It consisted
of applying profiles of average health expenditure per capita, provided for a base year by
Member States, to a population projection of Eurostat. The projections were run under the
assumption of constant age and gender-contingent demand and consumption of health care
over time. They were also made under two cost assumptions, i.e. expenditures per capita grow
exactly at the same rate as GDP per capita (which can be considered as neutral in
macroeconomic terms), and expenditures per capita increase at the same rate as GDP per
worker (to reflect labour intensity of the health care sector).
The 2001 report of the EPC recognised the limitations of this projection methodology, in
particular the strong assumption of holding age-related expenditure profiles constant over
time, the failure to link expenditure to years of remaining life (death-related costs), and the
absence of non-demographic drivers of spending from the projection exercise.
53
In April 2004, the ECOFIN Council held a discussion on approaches to achieving a better control of health
care spending on the basis of a note by DG ECFIN, see ‘Controlling health care expenditures: some recent
experiences with reform’, Note from DG ECFIN for the attention of the Economic Policy Committee,
ECFIN/157/04 Rev.1 of 16 March 2004. Discussions subsequently took place on similar topics at a jointmeeting of Finance and Health Ministers organised by the OECD in May 2004, and also at a meeting of G8
Finance Ministers in June 2004. The issue of factors driving health care expenditures was also, under the
Dutch Presidency, addressed by Health Ministers, see ‘Health care in an ageing society: a challenge for EU
countries’, Background Paper of the Netherlands EU Presidency for the Informal Health Council in
Noordwijk, 9-10 September 2004.
110
Box 1. The importance of health care spending
The focus on health care spending in discussions on budgetary management and on the overall sustainability of
public finances is hardly surprising given its size and past trends. Total health care spending, both public and
private, as a share of GDP has been rising steadily in most EU Member States in recent decades, see Table 1. It
increased rapidly during the 1960s and 1970s, continued growing in most countries, although at a slower rate, in
the 1980s, and picked up again in the 1990s. Total spending on health as a proportion of GDP grew in the 1990s
in all Member States except Finland, Luxembourg, Denmark and Sweden. Currently, total spending in the EU on
health care ranges from 5.0% (LV) to 10.9% (DE) of GDP. A clear catch-up process in total health care spending
has been visible in European countries over the last decades, as the countries with the lowest initial rates of
expenditure have seen them rising considerably up to the levels comparable to those of most other Member
States.
Table 1. Total expenditure (public and private) on health care as % of GDP
BE
CZ
DK
DE
EE
GR
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
1970
4,0
:
:
6,2
:
6,1
3,6
5,4
5,1
:
2,7
:
:
3,6
:
:
:
5,1
:
2,6
4,2
:
5,6
6,9
4,5
1980
6,4
:
9,1
8,7
:
6,6
5,4
7,1
8,4
:
2,8
2,1
:
5,9
:
:
7,5
7,4
:
5,6
4,4
:
6,4
9,1
5,6
as % of GDP
1990
7,4
4,7
8,5
8,5
:
7,4
6,7
8,6
6,1
7,9
4,5
2,5
3,3
6,1
:
:
8,0
7,0
4,9
6,2
5,6
:
7,8
8,4
6,0
2000
8,7
6,6
8,4
10,6
5,5
9,9
7,4
9,3
6,3
8,1
6,0
4,8
6,0
5,5
7,1
8,8
8,3
7,6
5,7
9,2
8,0
5,5
6,7
8,4
7,3
2002
9,1
7,2
8,8
10,9
5,1
9,8
7,6
9,7**
7,3
8,4
6,4
5,0
5,7
6,1
7,8
9,6
9,3
7,6
6,0
9,3
8,2*
5,7
7,2
9,2
7,7
70-80
2,4
:
:
2,5
:
0,5
1,8
1,7
3,3
:
0,1
:
:
2,3
:
:
:
2,3
:
3,0
0,2
:
0,8
2,2
1,1
change
80-90
1,0
:
-0,6
-0,2
:
0,8
1,3
1,5
-2,3
:
1,7
0,4
:
0,2
:
:
0,5
-0,4
:
0,6
1,2
:
1,4
-0,7
0,4
90-00
1,3
1,9
-0,1
2,1
:
2,5
0,7
0,7
0,2
0,2
1,5
2,3
2,7
-0,6
:
:
0,3
0,6
0,8
3,0
2,4
:
-1,1
0,0
1,3
*2001
**estimate
Source: European health for all database (HFA-DB), World Health Organization Regional Office for Europe (data on EE, CY, LV, LT, MT,
SI); OECD HEALTH DATA 2005, (data on all other countries)
Broadly similar trends, including a catch-up process, are evident as regards public spending on health care, see
Table 2. As a share of GDP, public spending on health expenditure rose over the period 1970-1980 in all EU
countries for which data are available. In the 1980s, the increasing trend slowed down considerably and even
reversed in a few countries (IE, DK, SE, DE). In the 1990s, another five countries (FI, LU, PL, IT, NL) saw their
public expenditure falling, but in most other Member States average spending continued to grow. Judging by
public spending as a share of GDP, efforts to control public spending during the 1980s and especially the 1990s
have had some impact. In 2001, public spending as share of GDP was broadly 0.7% higher for the EU compared
with 1990, 0.5% higher compared with 1980 and 2.3% higher compared with 1970 (unweighted average of
available figures). There has also been a clear trend of narrowing dispersion in spending across countries, mainly
through the catch-up process in the countries with the lowest initial levels of expenditure, like PT, where public
spending on health grew from 1.5% of GDP in 1970 to 6.6% of GDP in 2002, ES (from 2.4% to 5.4%), or GR
(from 2.6% to 5.2%).
111
Table 2. Public expenditure on health as a share of GDP and of total expenditure on health, 1970 to 2001
Public health expenditure as % of total health expenditure
1970
1980
1990
2000
2002
:
:
:
71
71
97
97
97
91
91
:
88
83
83
83
73
79
76
79
79
:
:
:
77
76
43
56
54
54
53
65
80
79
72
71
76
80
77
76
76
82
82
72
73
75
:
:
79
74
76
35
52
40
35
37
:
:
100
74
68
:
:
90
72
72
89
93
93
90
85
:
:
:
71
70
:
:
:
54
69
:
69
67
63
63*
63
69
74
70
70
:
:
92
70
72
59
64
66
70
71
100
100
100
87
87*
:
:
:
89
89
74
79
81
75
76
86
93
90
85
85
87
89
84
81
83
Public health expenditure as % of GDP
1980
1990
2000
:
:
6,1
:
4,6
6,0
8,0
7,0
6,9
6,8
6,5
8,4
:
:
4,2
3,7
4,0
5,3
4,3
5,3
5,3
5,7
6,6
7,0
6,9
4,4
4,6
:
6,3
6,0
1,5
1,8
2,1
:
2,5
3,5
:
3,0
4,3
5,5
5,7
4,9
:
:
5,0
:
:
4,7
5,2
5,4
5,3
5,1
5,1
5,3
:
4,5
4,0
3,6
4,1
6,4
4,4
5,6
6,9
:
:
4,9
5,1
6,3
5,0
8,4
7,6
7,1
5,0
5,0
5,9
2002
6,5
6,6
7,3
8,6
3,9
5,2
5,4
7,4
5,5
6,4
2,3
3,4
4,1
5,2
5,5
6,6
5,8*
5,3
4,3
6,6
7,1*
5,1
5,5
7,8
6,4
70-80
:
:
:
2,3
:
1,1
2,0
1,6
2,7
:
0,5
:
:
2,3
:
:
:
1,9
:
2,1
0,2
:
0,9
2,5
1,1
Change
80-90
:
:
-1,0
-0,4
:
0,3
1,0
0,9
-2,5
:
0,3
:
:
0,2
:
:
0,2
0,1
:
0,5
1,2
:
1,3
-0,9
0,0
90-00
:
BE
1,5
CZ
DK
-0,1
1,9
DE
:
EE
GR
1,4
0,0
ES
0,5
FR
IE
0,2
-0,3
IT
0,3
CY
LV
1,0
1,4
LT
-0,7
LU
HU
:
:
MT
-0,1
NL
AT
0,1
-0,5
PL
2,3
PT
1,3
SI
:
SK
FI
-1,3
-0,4
SE
0,9
UK
*2001
Source: European health for all database (HFA-DB), World Health Organization Regional Office for Europe (public health expenditure as % of total health expenditure and public
health expenditure as % of GDP for EE, CY, LV, LT, MT, SI); OECD HEALTH DATA 2005 (public health expenditure as % of GDP for all other countries)
1970
:
:
:
4,5
:
2,6
2,4
4,1
4,2
:
0,9
:
:
3,2
:
:
:
3,2
:
1,5
4,2
:
4,1
5,9
3,9
In most countries spending on health care has accounted for a growing share of total public spending (see Table
3). This occurred not only during the 1970s and 1980s with the widening of access to public health care systems,
but especially during the 1990s. It has increased between 1990- 2003 in most countries by between 0 and 4.5
percentage points, again with the largest growth in the catch-up countries (GR, PT, IE). Currently, it ranges from
6.4% in SK to 20.9% in IE.
Table 3. Spending on health as % of total primary government spending, 1990-2002
as % of total primary government spending
1990
1995
2000
2003
13,0
14,2
15,0
15,4
BE
:
:
:
12,6
CZ
13,6
13,0
13,3
13,5
DK
13,3*
12,2
14,7
14,3
DE
:
:
:
11,4
EE
2,6
9,0
7,5
6,8
EL
:
:
14,7
14,5**
ES
:
15,3
15,7
16,5**
FR
16,1
17,1
19,0
20,9**
IE
14,5
12,8
15,0
14,8
IT
:
:
7,1
7,5
CY
:
:
:
9,3
LV
:
:
:
13,2
LT
11,0
12,3
11,0
11,8
LU
:
:
:
12,3
HU
:
:
13,1
13,7
MT
:
7,8
9,6
9,8
NL
:
14,7
16,1
13,8
AT
:
:
:
7,3
PL
11,8
15,1
16,2
15,8
PT
:
:
:
14,7
SI
:
:
:
6,4
SK
:
:
:
13,3
FI
:
10,4
11,9
12,9
SE
13,2
13,7
15,5
16,3
UK
* 1991 and 91-95
** 2002 and 00-02
Source: Eurostat
90-95
1,2
:
-0,6
-1,1*
:
6,4
:
:
1,0
-1,7
:
:
:
1,3
:
:
:
:
:
3,3
:
:
:
:
0,5
change
95-00
0,8
:
0,4
2,5
:
-1,5
:
0,4
1,9
2,2
:
:
:
-1,3
:
:
1,9
1,4
:
1,1
:
:
:
1,4
1,8
00-03
0,4
:
0,2
-0,4
:
-0,7
-0,2**
0,8**
1,9**
-0,2
0,5
:
:
0,8
:
0,6
0,2
-2,3
:
-0,4
:
:
:
1,1
0,8
112
Contribution to the work on health care projections
The decision to include non-demographic factors in the projection exercise substantially
added to the complexity of the projection exercise. As a first step, DG ECFIN carried out a
literature survey on the drivers of health care spending and methodologies that have used to
project health care spending54. DG ECFIN also organised a conference jointly with the Health
Division of the OECD on 21/22 February 2004 entitled Understanding trends in disability
among elderly populations and the implications of demographic and non-demographic
factors for future health and long-term care costs55. The Commission has also received
valuable input from Ilija Batljan (University of Stockholm) and Adelina Comas-Herrera
(PSSRU, London School of Economics and Political Science) who were visiting fellows with
DG ECFIN in 2005. Several AWG members also provided written contributions to the work
of the group56.
Outline of this chapter
The remainder of this chapter is structured as follows. The next section provides an overview
of the different approaches used to project health care spending and the sensitivity tests.
Section 4.3 describes the data needed to run the projections. Section 4.4 presents the
projection results: it starts with the projections results for a pure ageing scenario that is
identical to the projection methodology used in 2001. It then presents the results for different
sets of projections that examine additional drivers of health care spending, including scenarios
looking at the health status of elderly citizens, death-related costs, the impact of changes in
real income and finally at the evolution of unit costs. Section 4.5 contains an overall
assessment of the budgetary projection results for all scenarios and contains policy
conclusions. Four annexes are also included. Annex 4 describes the projection methodologies
in more detail. Annex 5 provides information and analysis on the data inputs. Annex 6
presents a series of additional sensitivity tests the results of which should be seen as a
complement to the analysis done in the report. Annex 7 contains tables with the detailed
projection results for all discussed scenarios.
4.2.
Short overview of the projection methodology
Capturing the various demographic and non-demographic drivers of spending
54
‘Factors driving public expenditures on health/long-term care over the long run and an overview of
methodologies used to make expenditure projections’, Note for the attention of the AWG meeting of 18/19
April 2005, ECFIN/REP51821/05-EN of 15 April 2005.
55
The presentations and papers circulated at the conference can be downloaded from: the DG ECFIN web-site at
http://europa.eu.int/comm/economy_finance/events/2005/events_brussels_0205_en.htm
56
Englert M. (2004), ‘Assessing the budgetary cost of ageing and projecting health care (+care for the elderly)
expenditure’, Federal Planning Bureau of Belgium, presentation to the joint AWG-OECD meeting of 3 June
2004. Englert M., M.J. Festjens, M.Lopez-Novella (2004), L’évolution à long terme des dépenses de soins
de santé, Journée d’Etudes: ‘Budget 2005’, Institut Belge des Finances Publiques. Madsen M. (2004)
‘Methodologies to incorporate ‘death related costs’ in projections of health and long-term care based on
Danish data’, Ministry of Finance, Denmark dated 4 November 2004. Note for the attention of the AWG
meeting of 8/9 November 2004. Ragioneria Generale dello Stato (2004b) ‘How to take account of deathrelated costs in projecting health care expenditure – the evidence from Italy and a proposal for the EPCAWG’, Note for the attention of the AWG meeting of 10 March 2004.
113
Health care spending is determined by a complex series of demand and supply side factors.
These were extensively reviewed in EPC and European Commission (2005b). According to
the literature, the demand for health care depends ultimately on the health status and
functional ability of (elderly) citizens, and not on age per se. While age is a useful indicator of
the health status of an elderly population (and shown by the steep upward slope of age-related
expenditure profiles)57, it is not the causal factor. Health care spending is therefore mostly
driven by:
• the health status of the population (see box 2 below);
• economic growth and development;
• new technologies and medical progress;
• the organisation and financing of the health care system;
• health care resource inputs, both human and capital.
Box 2. Healthy life expectancy – will the extra years of life be spent in good health and free of disability?
There is debate in literature on the extent to which, as life expectancy increases, the health status (or morbidity)
of the population may change. Traditionally, a decrease in mortality rates was considered to reflect the
improvement in the health status of the population, i.e. a decrease in morbidity. When reliable empirical
evidence (life-tables, precise data on mortality, disability and morbidity) became available, this simple
relationship was not supported by the data. Three main hypotheses have emerged in the literature which are
illustrated on the graph 1 below (for an overview of existing theories see Nusselder (2003)).
Graph 1. Different hypothesis for the evolution of healthy life expectancy
D yn am ic e q u ilib riu m
Year 2004
Year 2050
M o rb id ity /d is a b ility ex p an s io n
Year 2004
Year 2050
M o rb id ity /d is a b ility co m p ress io n
Year 2004
Year 2050
In cr e as e in life e xp e ctan cy
0
10
20 in good
30 health
40
Years
s pent
50
60
70
80
90
Years s pent in bad health (w ith m orbidity/dis ability)
Source: DG ECFIN
57
Recent evidence, based on the data from a set of industrialised countries, shows that total health care
provided to an average person over 65 years of age costs 2.7 to 4.8 times as much as health care provided to
an average person aged 0-64 (Anderson and Hussey 2000). In other words, 35-50% of total health
expenditure is spent on elderly people (Jacobzone 2002).
114
The expansion of morbidity hypothesis was proposed by Gruenberg (1977), Verbrugge (1984) and Olshansky et
al (1991) and empirically supported by Guralnik (1991). It posits that as life expectancy increases, older people
become more vulnerable to chronic diseases and spend more time in ill-health (represented by the dark shaded
area on showing that most of the additional gains in life expectancy are spent in bad health). In other words, a
higher proportion of people with health problems survive to an advanced age. This relationship works mainly
through three mechanisms:
• thanks to medical interventions, the prolonged survival of chronically ill people increases their lifespan but it
does not improve their health state. Consequently, extra years of life expectancy are, at least partially, spent
in bad health;
• increased survival means that a larger part of population is elderly and more vulnerable to chronic diseases:
moreover, the causes of disability are shifting from fatal to non-fatal diseases which are more prevalent in
older age cohorts;
• chronic disease can act as a risk factor for other illnesses. For example, a disease earlier in lifetime can have
negative consequences later on: a non-fatal disease may not translate directly into higher mortality but into
higher morbidity and disability.
The dynamic equilibrium hypothesis was proposed by Manton et al. (1995). It posits that the postponement of
death to higher ages due to falling mortality is accompanied by a parallel postponement of morbidity and/or
disability. Consequently, healthy life expectancy grows at the same rate as total life expectancy and the number
of years spent in bad health remains the same. On the graph, this is characterised by the number of years in good
health (the lighter shade) increasing by the same amount as life expectancy at birth: hence, the total period spent
in bad health during a lifetime is unchanged. The term ‘dynamic equilibrium’ is meant to capture the overall
changes in life expectancy and severe disability, and this hypothesis is a simplified version of a more
sophisticated theory proposed earlier by Manton (1982), which argued that an increased survival may lead to an
increase in the number of years spent in bad health. However, the time spent with severe morbidity and disability
remains approximately constant due to the fact that medical treatments and improvement in lifestyles reduce the
rate of progression of chronic diseases. Thus, not everybody will enjoy the benefits of all gains in life expectancy
being spent in full health. Instead, part of the gains in life expectancy may be spent in moderate health and the
prevalence of chronic illness may increase; however, severe disability which is connected to the most costly part
of health care services may be postponed to the final phase of life (meaning that age-related disability rates could
decline). These effects may cancel out so that the average number of years spent in morbidity would remain
unchanged.
The compression of morbidity hypothesis was proposed by Fries (1980, 1983, 1989, 1993), posits that as life
expectancy increases the onset of disability will be postponed to an high ages thanks to improved living
conditions, healthier lifestyles and the fact that more and more chronic diseases may be curable. According to the
hypothesis, humankind has a genetically determined — albeit individually variable — limit to the lifespan and
while life expectancy is increasing, it is approaching that limit (a hypothesis rejected later by several authors
including Oeppen and Vaupel 2002, Robine and Vaupel 2002, Robine et al. 2005). Accordingly, morbidity and
disability will be gradually compressed at very old ages (into the last years of life) and the number of years spent
with diseases or disabilities will decrease over time. The graph above represents this by decreasing the total
period spent in bad health during a lifetime. Thus, health life expectancy grows by more than life expectancy at
birth.
Recent studies have not provided strong evidence in favour of any of the above hypothesis. Results have differed
significantly not only across countries, but also across sexes. Batljan and Lagergren (2000) found that even if
existing state of research does not allow for any conclusive statements, most empirical data support the
hypothesis of morbidity postponement.
Given these considerations, the need to include non-demographic factors in the projection
exercise was recognised58. Table 4-1 provides an overview of the different drivers of
spending, and how they are captured within this budgetary projection exercise.
58
EPC and European Commission (2005b).
115
Table 4-1 The drivers of health care spending: how they are incorporated in the projection exercise
Demand side factors
Mechanism/channel through which health
care spending is affected
Size and age
Population size and age structure determines
structure of the
the overall number of persons who
population
potentially need some health care services.
Morbidity rates tend to increase sharply at
older ages, although age itself is not the
causal factor.
Health care
Changes in age-specific mortality rates will
status of the
alter the demand for health care.
population,
especially of
elderly cohorts
Death related
costs
Large share of total health are spending is
concentrated in the final phase of life linked
to approaching death.
Income
If health care services are a luxury good,
then the income elasticity of demand would
be greater than one, and health care spending
as % of GDP should increase if real living
standards improve.
Evidence in literature on likely impact on
spending
Population projections show large increase
in the number of older persons.
Addressed in projections
No clear cut evidence as to whether the
health care status of elderly is static
(expansion of morbidity hypothesis) or
improving (dynamic equilibrium or
compression of morbidity hypotheses).
Constant health scenario (II)
and improved health scenario
(A-II).
Large body of evidence confirming the
existence of death-related costs, and that the
ratio of spending between decedents and
survivors declines with age. No clear
evidence on whether the importance of
death-related costs has changed over time.
Studies at micro level show income
elasticity of demand greater than 1 but
neutral at an aggregate level.
Real convergence process may lead to an
increase in health care spending as a result
of absolute increase in demand and a shift
towards high quality medical goods and
services demanded in fast growing
economies.
Death-related cost scenario
(III).
Pure ageing scenario (I) plus
high life expectancy scenario
(A-I).
Scenario IV considers an
income elasticity of demand
greater than 1 for all Member
States. Scenario A-III considers
the convergence in age-related
expenditure profiles in EU10 to
EU15 levels.
Likely effect on
projection results
The ‘pure’ effect of an
ageing population will
lead to strong pressure
for increased
spending.
Future improvements
of health care status
will lower the
projected impact on
spending compared
with a pure ageing
scenario.
Reduces projected
increases in spending
compared with pure
ageing scenario.
Projected increases in
spending compared
with pure ageing
scenario.
Supply side factors
Technology
Relative costs in
the health care
sector
Government
policy and
institutional
settings
Mechanism/channel through which health
care spending is affected
Technology can lower unit costs of
providing more efficient treatment, but can
push up total spending by making new
treatments available for more persons.
Technology can lower the demand for health
care if early or less invasive interventions
improve health care status and lower future
health care needs: alternatively, it can
increase future health care needs by
increasing the survival probabilities of
persons with chronic or multiple health
conditions.
Total health care spending driven by the
evolution of unit costs for key components
(wages, capital investment and
pharmaceuticals) relative to the economy as
a whole.
Overall spending on health determined by
policy choices on access to health care
systems and on quality (waiting times,
patient choice etc.) The evolution of
spending is also determined by the
effectiveness of aggregate budgetary control
measures (e.g. spending caps) and micro
incentives for patients and health care
professionals favouring rational resource
use. Real convergence process also plays a
role in designing appropriate health policy
setting.
Evidence in literature on likely impact on
spending
Not clear cut. Evidence to date suggests that
technology has pushed up overall spending as
increased demand appears to have outweighed
unit cost savings. However, there is
considerable uncertainty on future prospects.
Prospective technological developments could
radically alter treatment possibilities and the
health care sector is starting to catch-up with
other sectors on the deployment of IT.
Unclear due to data limitations and prevalence
of non-market pricing in the health care sector.
Wages often covered by collective agreements
and pharmaceutical prices are regulated.
Evidence from US points to high price
inflation for pharmaceuticals but this may be
driven by incentives embedded in their market
structure.
Improved access has been major driver of
spending in past decades. Governments face
strong pressure to provide access to new
medical treatments and to improve quality of
services, and existing projections from
national sources show that policy choices have
a major impact on health care spending.
Aggregate budgetary control measures appear
to have stemmed increases in health care
spending in the 1990s, but long-term
effectiveness will require appropriate micro
incentives.
Addressed in projections
Likely effect on
projection results
Not modelled. All scenarios
implicitly assume a neutral
impact of technology on
spending.
From fast cost growth scenario
(A-IV), and extrapolation
scenario (A-V), one could infer a
pessimistic the impact of
technology (the effects of
increased demand outweigh unit
cost reductions).
Unit cost – GDP per worker
scenario (V), fast cost growth
scenario (A-IV), and
extrapolation scenario (A-V).
Can push up (fast
growth scenario)
or reduce (slow
growth scenario)
projected spending
compared with
pure ageing
scenario.
Not modelled
117
Six different types of scenarios
Rather than trying to construct an all-encompassing projection methodology to capture all
demographic and non-demographic factors, it was agreed to run several different projection
scenarios in order to tackle the issue from a variety of different angles. An overview of all
approaches is presented in Table 4-2 below.
• Pure ageing scenario (I): this scenario attempts to isolate the “pure” effects of an ageing
population on health care spending. It is a repetition of the methodology used in the 2001
AWG budgetary projection exercise. It assumes that age-related spending per capita on
health care in the base year (2004) remains constant over time. This way all gains in life
expectancy are assumed to be spent in bad health while the number of years spent in good
health remains constant. As such, this scenario is inspired by the ‘expansion of morbidity’
hypothesis in the literature, as it de facto would assume that the gains in life expectancy up
to 2050 are assumed to be spent in bad health. The constant age profile is applied to the
baseline AWG population scenario (described in chapter 2.1) with an assumption that the
costs evolve in line with GDP per capita (see table 5-4 in annex 5). Annex 4 describes the
projection methodology in more detail;
• A constant health scenario (II) considering the health status of elderly citizens: as
pointed out above, the pure ageing scenario may be pessimistic in that they implicitly
assume that a large share of the gains in life expectancy up to 2050 would be spent in bad
health. The constant health scenario is inspired by the ‘dynamic equilibrium’ hypothesis
and captures the potential impact of possible improvements in the health care status of
elderly citizens. It assumes that the number of years spent in bad health during a life time
in 2050 is identical to that in 2004, i.e. all future gains in life expectancy are spent in good
health. This assumption is modelled by progressively shifting the age-related expenditure
profile of the base year outwards in direct proportion to the projected gains in age and
gender specific life expectancy, embedded in the baseline population projection (see tables
5-2 and 5-3 in annex 5). This procedure is illustrated on Graph 4-1 by the straight dark
line, which illustrates the age-related expenditure profile that would be applied in the year
2050.
Average expenditure per head expressed in euros
Graph 4-1 Illustration of the different scenarios for future morbidity/disability and
longevity using age profiles on health care costs
5000
4000
3000
2000
1000
0
0
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Year 2004 (Unchanged) = Year 2050 (Pure Demographic Scenario)
Year 2050 (Constant Health Scenario)
Year 2050 (Improved Health Scenario)
Source: DG ECFIN
• A death-related costs scenario (III) links health care spending to years of remaining life.
There is strong evidence that a large share of total spending on health care during a
person’s life is concentrated in the final years of life. Based on data available supplied by
AWG members, a profile of “death related” costs by age has been constructed, with unit
costs differentiated between decedents (those who die within a calendar year) and
survivors (for empirical evidence on death-related costs, see section 4.3.).
• A scenario looking at income effects (IV): a key question concerns the income elasticity
of demand for health care, and whether it is greater than unity. Scenario IV is identical to
the pure ageing scenario (I) except that the income elasticity of demand is equal to 1.1 in
the base year and converges in a linear manner to 1 by the end of projection horizon in
2050. The elasticity coefficient at the beginning of the period has been chosen arbitrarily,
although taking account of empirical evidence on developments in this value over the
recent decades (see discussion in section 4.3.).
• A scenario where costs evolve in line with GDP per worker (V) is identical to the pure
ageing scenario (I) except that costs are assumed to evolve in line with the evolution of
GDP per worker (see table 5-5 in annex 4). As wages are projected to grow faster than
GDP per capita, this scenario provides an insight into the effects of unit costs in the health
care sector increasing by more than in the economy as a whole. This is identical to a
scenario run in 2001 budgetary projection exercise;
• An AWG reference scenario (VI): this scenario combines a number of the elements in the
scenarios described above. In particular, it aims at incorporating death-related costs and the
impact of income elasticity exceeding unity on health care spending. Both theoretical
discussion and empirical results presented in scenario III suggest that incorporating deathrelated costs is expected to drive total costs of health care down from the level predicted by
pure ageing scenario by somewhat less than the assumption of changes in health status
119
embedded in constant health scenario does. However, given very scarce and hardly
comparable data on death-related costs, it cannot be considered as reliable enough to be
used in the reference scenario. Instead, an intermediate scenario between pure ageing and
constant health scenario has been calculated by assuming health status of the populations
will improve, but only by half as much as in constant health scenario. This assumption has
been complemented by adding the effect of income elasticity equal to 1.1 in the base year
and converging to 1 by 2050. This scenario was developed so as to provide a prudent
central reference scenario for undertaking policy analysis at EU level.
Additional scenarios for public spending on health care are presented in annex 6. They look at
the impact of a higher than expected life expectancy, an improved health scenario where
health life expectancy increases by more than life expectancy (inspired by the compression of
morbidity hypothesis), an EU10 cost convergence scenario where average unit costs of health
care provision in the EU10 Member States evolve over time to reach the EU15 cost structure,
a fast cost growth scenario, and a projection where unit costs for the different components of
health care spending evolve in line with past trends.
Table 4-2 Overview of different approaches used to make the projections on health care
spending
Population
projection
Age-related
expenditure
profiles
Unit cost
development
Income
elasticity of
demand
Pure ageing
I
Constant health
II
Death related
costs
III
AWG scenario baseline
AWG scenario baseline
AWG scenario baseline
Income elactity Unit costs - GDP
of demand
per worker
IV
V
AWG reference
scenario
VI
AWG scenario baseline
AWG scenario baseline
AWG scenario baseline
Intermediate
between pure ageing
Constant health
and constant health
scenario whereby Constant 2004
2004 profiles held 2004 age profile profiles but split 2004 profiles held 2004 profiles held scenarios, whereby
constant over
shifts in line with into spending on
constant over
constant over
2004 age profile
projection period changes in age- decedents and projection period projection period
shifts by half the
specific life
survivors
change in ageexpectancy
specific life
expectancy
GDP per capita
GDP per capita
GDP per capita
GDP per capita
1
1
1
1,1 in base year
converging to 1
by 2050
GDP per worker
GDP per capita
1
1,1 in base year
converging to 1 by
2050
120
4.3.
Data used in the projections
A cross country comparison of health care spending per capita.
As discussed above, although age is not the causal factor which drives changes in health care
spending, the developments of the two variables over an individual’s lifespan may be linked
according to the general pattern which is broadly uniform across the countries. This pattern
can be graphically presented as the age-related expenditure profile, showing the average
spending on health care for each age cohort.
It is important to keep in mind that age-related expenditure profiles are not direct measures of
morbidity or the need for health care services. They also encompass measures of other
demand and supply factors that affect health care use, such as availability of services and
treatments and age-related rationing. In effect, it is assumed that spending on health care is a
proxy for morbidity, which changes proportionately to the evolution of the number of years
spent in bad health: this assumption is needed as no reliable quantitative indicator of
morbidity is available, especially one which is comparable across Member States.
Graph 4-2 presents the age-related expenditure profiles for Member States for which data is
available. In brief, profiles were reported for the 2005 exercise by eighteen Member States
(BE, CZ, DK, DE, ES, IT, LV, LT, LU, MT, NL, AT, PL, SI, SK, FI, SE, UK). Table 4-3 and
Table 4-4 present some key figures on age-related expenditure, both in nominal terms and as
% of GDP per capita, for certain male and female older age cohorts. Based on this data (see
annex 5.1 for more details), the following remarks are warranted:
• in nearly all Member States, and for EU15 and EU10 aggregate, age-related expenditures
for older cohorts are higher for males than for females;
• nominal spending on health is much higher in EU15 than EU10 countries. For example, in
EU15 countries (excluding IE), for males aged 60-65, average spending amounted to
€2117 and €1939 for females compared with €544 and €494 respectively in EU10
countries (excluding EE, CY, HU and MT). This gap grows with age. Average nominal
spending for the cohort aged 60-64 in the EU15 is 4 times higher than in EU10 countries:
this grow to 7 times higher for the cohort aged 90-94.
• expressed as a share of per capita GDP, there is an apparent difference in the age-related
spending profiles between EU15 and EU10 countries59. First, in most EU15 countries,
spending peaks at between 15 and 20% of per capita GDP compared to between 5 and 15%
in available EU10 countries. Secondly, peak spending occurs somewhat later in EU15
countries in the cohort aged 85 to 90 compared with the EU10 where it occurs in the 75-80
cohort. Thirdly, there appears to be a much sharper tailing-off in spending for the oldest
age-cohorts in EU10 countries, although the EU15 unweighted average figure is influenced
by ‘outlying’ results for the UK and FI and considerable variation of data across the EU10
Member States. Spending for people aged 90-94 is on average 2.4 times higher than for
people aged 60-64 in EU15 countries. In contrast, EU10 countries spend on the 90-94
years old only slightly more (120-130%) than on the 60-64 cohort.
59
A significant exception is Malta where the shape of the age profile resembles much more that of the average
EU15 country. This is why Maltese data has not been taken into account when calculating EU10 average
profile. Furthermore, in all scenarios where composite age profiles are used both Malta and Cyprus have
been assigned the EU15, rather than EU10, average profile.
Graph 4-2 Age related expenditure profiles for EU Member States, males and females
Males - EU15
Males - EU10
SI
CZ
SK
10%
LV
LT
90
80
-9
4
10
0+
4
4
-8
4
-7
70
-6
SK
LV
LT
PL
-9
90
CZ
LV
LT
PL
SK
MT
SI
10
0+
4
4
4
-8
80
4
-7
-6
60
70
4
4
-5
50
-4
40
30
-3
4
4
4
0%
-2
4
0+
10
90
-9
4
4
-8
80
4
-7
-6
60
50
70
4
4
-5
4
-4
40
4
-3
30
-2
20
-1
4
0%
SI
CZ
10%
20
10%
20%
-1
DE
GR
AT ES
FR
NLDK
LU
ITPT SE
BE
MT
-4
20%
30%
0
FI
BE
DK
DE
GR
ES
FR
IT
NL
AT
PT
FI
SE
UK
LU
10
UK
-4
4
50
Females - EU10
30%
0
60
-4
40
30
-5
4
4
4
-3
4
Females - EU15
10
CZ
LV
LT
PL
SK
MT
SI
PL
0%
-2
-9
90
80
70
4
10
0+
4
4
-8
4
-7
4
-6
60
50
40
30
-5
4
4
-4
4
-3
4
20
-2
-1
10
0
-4
0%
20%
20
10%
MT
-4
GR
AT
DE
ES
DK LU
NL PT
IT
BESE
30%
-1
FR
20%
BE
DK
DE
GR
ES
FR
IT
NL
AT
PT
FI
SE
UK
LU
0
FI
10
UK
30%
Source: National data
122
Table 4-3 A comparison of the age-related expenditure profiles – males
BE
CZ
DK
DE
EE
GR
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
EU15 average*
Cohort aged 60-64
Level in
Level as %
nominal
of per
euros
capita GDP
1880
6,9
975
11,5
4384
12,2
2366
9,0
497
7,6
1271
8,5
1676
8,5
2222
8,2
2800
7,7
2166
9,3
1314
7,7
373
7,9
319
6,1
3543
6,2
605
7,6
847
7,8
2201
7,7
2524
8,8
200
3,9
703
5,5
865
6,7
531
8,6
1907
6,6
1759
5,7
1038
3,6
2117
7,6
Cohort aged 70-74
Level in
Level as %
nominal
of per
euros
capita GDP
2933
10,8
1405
16,6
5307
14,7
3539
13,4
687
10,5
2245
15,0
2424
12,3
3496
12,9
4514
12,5
3471
14,9
2119
12,5
517
10,9
406
7,8
5725
10,1
836
10,5
1312
12,0
3409
11,9
3811
13,3
280
5,5
1379
10,7
1692
13,0
723
11,7
3681
12,8
2632
8,5
3053
10,7
3365
12,3
Cohort aged 80-84
Level in
Level as %
nominal
of per
euros
capita GDP
3941
14,5
1449
17,1
5252
14,6
5091
19,3
690
10,6
2840
19,0
3196
16,2
6039
22,3
6034
16,6
3846
16,5
2833
16,6
605
12,8
423
8,1
7477
13,2
840
10,6
1839
16,8
4289
15,0
4811
16,9
259
5,1
1915
14,9
1790
13,8
598
9,7
5034
17,5
3936
12,7
4940
17,3
4472
16,4
Cohort aged 90-94
Level in
Level as %
nominal
of per
euros
capita GDP
4330
15,9
972
11,5
5154
14,3
4442
16,8
503
7,7
2840
19,0
3196
16,2
6039
22,3
6567
18,1
3163
13,5
3083
18,1
355
7,5
308
5,9
8646
15,2
612
7,7
4190
38,4
4193
14,7
4673
16,4
196
3,8
1915
14,9
1802
13,9
598
9,7
7388
25,8
4916
15,8
8599
30,1
4964
17,9
standard deviation*
950
2,1
1130
2,0
1386
2,6
2064
EU10 average**
544
7,5
837
10,9
854
11,1
705
8,7
standard deviation**
312
2,6
577
3,9
616
4,3
604
3,7
EU25 average***
1607
7,6
2545
11,9
3313
14,9
3710
16,3
standard deviation***
1077
2,1
1528
2,6
2051
3,9
2585
7,9
4,8
* unweighted average calculated without IE
** unweighted average calculated without EE, CY, HU, MT
*** unweighted average calculated without EE, IE, CY, HU
Note: For the countries with no individual age profile available, composite EU15 (IE, CY) or EU10 (EE, HU) age profiles applied
Table 4-4 A comparison of the age-related expenditure profiles – females
BE
CZ
DK
DE
EE
GR
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
EU15 average*
Cohort aged 60-64
Level in
Level as %
nominal
of per
euros
capita GDP
1759
6,5
850
10,1
3564
9,9
2141
8,1
431
6,6
781
5,2
1462
7,4
2037
7,5
2518
6,9
1694
7,3
1182
6,9
289
6,1
261
5,0
3646
6,4
524
6,6
847
7,8
2201
7,7
2317
8,1
167
3,3
878
6,8
869
6,7
526
8,5
1875
6,5
1760
5,7
1038
3,6
1939
6,9
Cohort aged 70-74
Level in
Level as %
nominal
of per
euros
capita GDP
2593
9,5
1161
13,7
4216
11,7
3164
12,0
566
8,7
1677
11,2
2334
11,8
2677
9,9
3854
10,6
2511
10,8
1810
10,6
398
8,4
322
6,2
5249
9,3
689
8,7
1312
12,0
3409
11,9
3284
11,5
214
4,2
1145
8,9
1686
13,0
669
10,9
2842
9,9
2637
8,5
3053
10,7
2914
10,5
Cohort aged 80-84
Level in
Level as %
nominal
of per
euros
capita GDP
3727
13,7
1187
14,1
5348
14,8
4843
18,4
541
8,3
2758
18,4
2827
14,3
3857
14,2
5392
14,9
2889
12,4
2532
14,9
407
8,6
308
5,9
6972
12,3
658
8,3
1839
16,8
4289
15,0
4297
15,1
198
3,9
1427
11,1
1777
13,7
553
9,0
4596
16,0
3960
12,8
4940
17,3
4052
14,7
Cohort aged 90-94
Level in
Level as %
nominal
of per
euros
capita GDP
3804
14,0
1018
12,0
5157
14,3
5042
19,1
440
6,7
2758
18,4
2827
14,3
3857
14,2
6110
16,9
2568
11,0
2869
16,9
247
5,2
228
4,4
7244
12,8
535
6,7
4190
38,4
4193
14,7
4215
14,8
157
3,1
1427
11,1
1753
13,5
553
9,0
8001
27,9
4761
15,3
8599
30,1
4604
16,6
standard deviation*
853
1,5
1001
1,2
1347
2,2
2100
EU10 average**
494
6,6
741
9,4
738
9,2
659
7,9
standard deviation**
307
2,4
574
3,8
617
4,1
624
4,3
EU25 average***
1474
6,9
2217
10,3
3000
13,2
3457
15,1
978
1,7
1329
2,2
1911
3,8
2502
8,4
standard deviation***
5,7
* unweighted average calculated without IE
** unweighted average calculated without EE, CY, HU, MT
*** unweighted average calculated without EE, IE, CY, HU
Note: For the countries with no individual age profile available, composite EU15 (IE, CY) or EU10 (EE, HU) age profiles applied
123
To be able to make projections for health care spending for all EU25 Member States, the
following approach has been used for countries which did not provide age-related expenditure
profiles to the AWG:
• profiles reported for the 2001 exercise adjusted to 2004 by applying GDP per capita
growth rate have been used for three Member States (FR, GR, PT);
• for four countries (EE, IE, CY, HU) where no profiles exist, an ‘average profile’ was used,
calculated as the unweighted average of per capita expenditure expressed as % of GDP per
capita. Two separate profiles were established for EU10 and EU15, as there is a clear
difference in the shape of the curve between the Old and the New Member States. As
shown on Graph 4-3, the share of GDP per capita spent on health care is comparable, but
the shape shows an increasing gap in spending on people in their older ages.
• Actual data on total spending on health care have been reported by Member States and
used in the base year of the projection.
Graph 4-3 Average age-related expenditure profiles for the EU15 and EU10 (males and
females)
% of GDP per capita
20%
15%
10%
5%
males - EU15
females - EU15
males - EU10
10
0+
-9
4
90
-8
4
80
4
-7
70
60
-6
4
-5
4
50
-4
4
40
4
-3
30
-2
4
20
-1
4
10
0
-4
0%
females - EU10
Source: National data
Available empirical evidence on death-related costs
An item that deserves a special consideration in the present long-term projections of health
care expenditure is incorporation of death-related costs (or costs related to the number of
remaining years of life) to the projection methodology, which is a significant step forward in
comparison to the previous round of projections.
The rationale behind stems from empirical evidence that the last years of life, irrespective of
how long people live, are associated with high health care costs. Consequently, the decline in
124
the number of people who, in a given age group, have few remaining years of life, results in
the fall in average health care cost for all age groups, except for the oldest age cohorts60.
To quantify the significance of death related costs, data is needed on the difference in health
care costs borne by decedents (people who are going to die within a predefined short period of
time) and survivors (people who are not in their terminal phase of life). Eight Member States
provided the AWG with data on death related costs from a variety of national sources, namely
BE, CZ, DK, ES, IT, NL, AT and PL (see annex 5.4 for more details on the data used as well
as additional estimates of death-related costs from academic sources). Table 4-5 and Table
4-6 summarise the general characteristics of available data from national sources on death
related costs for males and females respectively. In particular, it shows the ratio of spending
on a person of a particular age who dies within one year compared with a person who
survives that period. For example, spending on an average male child aged 0-4 who dies
within a particular year is on average 25.9 times higher compared with an average child of the
same age who survives.
There appears to be a clear pattern of decline in the ratio of spending on decedents to
survivors with age. Moreover, while the ratios diverge widely across countries at younger age
cohorts, there is less dispersion amongst older age cohorts where most deaths occur.
However, due to different methodologies of data gathering, calculation (e.g. ratio of decedents
to survivors differs when calculated on the basis of per capita and per patient spending) and
coverage (e.g. either only hospital patients or also other cases taken into account), the data
varies significantly across the Member States. For example, Spain61 and Austria62 appear to
be outliers for both males and females across all age cohorts, with a respectively much lower
and higher ratio compared with other countries.
Given the wide divergences in the report estimates of death-related costs, and taking account
of the fact that no data is available for the majority of Member States, the budgetary
projections for the death-related costs scenario were run, for all Member States on the basis of
“average” death-related costs profile calculated as unweighted average of available datasets (it
is shown in the final column of Table 4-5 and Table 4-6).
60
This observation shows that the proposed method is theoretically consistent with the so called ‘dynamic
equilibrium hypothesis’, according to which falling mortality rate (and thus growing life expectancy) for
each age cohort is associated with a parallel decline in morbidity/disability rate, which results in a fall in
health care spending in each age cohort.
61
The Spanish case provides an example of how sensitive are the results to changes in the methodology of
calculating ‘death-related costs’. The ratio used in the projections (ranging from around 7 for the age cohorts
5-35 to 1.3 for the 80+) is calculated by dividing per patient cost of decedents (patients) by the per patient
cost of survivors (patients). Meanwhile, using a different methodology of dividing the per discharge cost of
decedent (discharges) by the per capita cost of survival discharges, gives extremely different results,
ranging from 228 for age cohort 10-14 to 7 for the 80+.
62
Given lack of precise information about costs borne by people dying outside hospitals, Austria has provided
two sets of data according to two opposite (extreme) assumptions: in the first case deaths occurring outside
hospitals are assumed not to generate any costs at all, while in the second case death cases outside hospitals
are assumed to cause the same costs as those in hospitals. The ratio of costs borne by decedents to those of
survivors shows similar decreasing pattern with age, but differs significantly in value between the two
situations: while in the first dataset it ranges from 74.2 for age cohort 10-14 to 3.1 for the 85+, in the second
dataset it amounts to 121.6 for the aged 10-14 and 7.3 for the 85+.
125
Table 4-5 Ratio between cost borne by a decedent and a survivor, by age cohort - males
Males
0-4
5-9
10 - 14
15 - 19
20 - 24
25 - 29
30 - 34
35 - 39
40 - 44
45 - 49
50 - 54
55 - 59
60 - 64
65 - 69
70 - 74
75 - 79
80 - 84
85 - 89
90 - 94
95 - 99
100+
BE
12,1
33,3
27,7
10,7
8,9
9,4
13,6
14,3
12,4
11,0
10,1
9,5
7,4
5,5
4,5
3,3
2,8
2,1
1,7
1,4
0,7
CZ
34,5
55,3
74,0
31,0
17,1
19,1
23,1
20,2
19,2
16,8
11,0
8,1
7,2
5,4
4,3
3,5
2,8
2,3
2,3
2,3
2,3
DK
4,5
77,4
8,7
1,1
0,3
12,0
11,4
7,1
6,3
8,2
7,5
7,5
6,2
5,0
4,4
2,8
2,0
1,7
1,4
1,6
1,6
ES
3,4
6,4
6,9
4,1
3,3
3,9
3,2
2,8
2,6
2,3
2,3
2,2
2,0
1,8
1,7
1,6
1,3
1,3
1,3
1,3
1,3
IT
68,0
79,5
73,1
38,7
26,0
29,0
30,4
40,5
35,3
30,9
21,1
17,1
12,1
8,5
6,2
4,5
3,3
2,5
1,7
1,7
1,7
NL
31,7
39,6
26,9
21,6
47,4
38,0
25,3
26,7
17,0
15,1
14,2
8,8
8,3
6,4
5,1
4,1
3,4
3,0
2,5
2,0
2,0
AT
27,0
104,8
121,6
64,7
41,7
57,7
48,1
42,9
34,6
31,4
21,4
18,9
16,3
13,2
11,6
8,9
8,0
7,3
7,3
7,3
7,3
PL
25,7
47,0
40,7
29,5
23,0
27,4
21,2
18,3
13,6
11,1
8,9
7,8
6,6
5,6
4,5
3,9
3,3
3,0
2,9
3,0
3,0
EU average
25,9
55,4
47,4
25,2
21,0
24,6
22,0
21,6
17,6
15,9
12,1
10,0
8,3
6,4
5,3
4,1
3,4
2,9
2,6
2,6
2,5
Source: National sources with ECFIN calculations
Table 4-6 Ratio between cost borne by a decedent and a survivor, by age cohort females
Females
0-4
5-9
10 - 14
15 - 19
20 - 24
25 - 29
30 - 34
35 - 39
40 - 44
45 - 49
50 - 54
55 - 59
60 - 64
65 - 69
70 - 74
75 - 79
80 - 84
85 - 89
90 - 94
95 - 99
100+
BE
20,1
33,0
9,5
21,1
11,7
13,1
11,4
11,7
13,8
14,3
12,1
10,4
9,6
6,8
5,0
3,5
2,5
1,8
1,4
1,1
0,9
CZ
43,5
48,2
42,5
26,2
26,2
28,7
32,0
25,7
20,4
17,1
13,6
10,7
10,0
6,8
5,1
3,7
2,9
2,2
2,2
2,2
2,2
DK
4,0
58,4
14,5
1,3
0,3
12,1
12,7
6,0
5,9
7,2
7,0
6,8
6,0
5,0
4,3
2,9
2,1
1,7
1,4
1,8
1,8
ES
3,4
6,9
6,3
7,0
7,1
5,9
6,2
4,6
3,2
2,8
2,6
2,4
2,3
2,1
1,8
1,6
1,3
1,3
1,3
1,3
1,3
IT
79,5
163,0
101,4
46,7
32,5
25,5
28,4
37,2
40,7
31,5
26,9
23,7
16,8
11,9
8,2
5,4
3,8
2,6
1,7
1,7
1,7
NL
79,1
60,0
43,3
24,7
33,2
10,4
18,9
23,5
18,1
17,2
15,5
12,9
12,4
8,3
6,4
4,6
3,1
2,5
2,0
1,7
1,7
AT
39,1
153,0
120,4
69,1
87,3
41,3
33,4
29,6
33,9
28,0
25,7
22,0
20,6
15,0
11,0
8,9
7,1
6,5
6,5
6,5
6,5
PL
39,7
50,3
49,3
37,3
26,1
24,5
25,6
23,0
20,5
15,1
12,3
10,9
9,3
7,4
5,6
4,4
3,7
3,3
2,8
2,6
2,6
EU average
38,5
71,6
48,4
29,2
28,0
20,2
21,1
20,2
19,6
16,6
14,5
12,5
10,9
7,9
5,9
4,4
3,3
2,7
2,4
2,4
2,3
Source: National sources with ECFIN calculations
Income elasticity of health care spending – historical evidence
In order to analyse the past developments in income elasticity of health care spending and
find the value of elasticity which could be used in the projection exercise, a simple analysis of
the past trends has been done. For that purpose, the growth in health care spending over the
last 10, 20 and 30 years has been compared with GDP growth rate.
The results, based on the OECD Health Data 2005, are presented in the table below. Left
panel presents the elasticity of total spending on health care and right panel the elasticity of
public spending on health care for nineteen countries being members of the European Union
and the OECD.
126
Table 4-7 Elasticity of health care spending per capita with respect to GDP per capita
Total health care spending
2002-1992
2002-1982
2002-1972
1,88
1,28
1,56
Austria
3,34
1,45
2,34
Belgium
1,70
:
:
Czech Republic
1,40
0,92
1,11
Denmark
-0,40
1,14
1,25
Finland
1,91
3,20
1,76
2002-1980
2002-1970
France
-1,79
1,43
1,70
Germany
2,13
1,80
2002-1980
1,68
2002-1970
Greece
1,03
:
:
Hungary
1,08
0,93
1,21
Ireland
:
0,38
1,32
2002-1988
Italy
0,97
1,02
1,77
2002-1970
Luxembourg
1,65
1,28
1,41
Netherlands
0,96
:
:
Poland
3,15
1,77
2,93
Portugal
0,78
:
:
2002-1997
Slovak Republic
2,01
1,47
1,86
Spain
0,13
0,98
1,34
Sweden
1,39
1,49
1,73
United Kingdom
1,32
1,34
1,70
Unweighted average
1,25
0,30
0,48
Standard deviation
Public health care spending
2002-1992
2002-1982
2002-1972
0,55
1,15
1,73
:
:
:
1,59
:
:
1,37
0,84
1,09
-0,62
1,05
1,35
2,99
1,62
1,93
2002-1980
2002-1970
-0,93
1,44
1,78
1,79
1,63
2002-1980
2,08
2002-1970
0,55
:
:
1,19
0,85
1,21
0,84
1,22
:
2002-1988
0,70
0,92
1,70
2002-1970
0,65
1,07
1,46
0,85
:
:
4,72
2,29
3,49
0,56
:
:
2002-1997
0,26
1,28
1,99
0,32
0,85
1,32
1,33
1,40
1,63
1,04
1,26
1,75
1,27
0,40
0,61
Source: OECD Health Data 2005
Three different time periods have been analysed where available: last 10, 20 and 30 years by
2002 which is the latest year in which data for most Member States were available. The
availability of the data depends on the time period concerned. It is almost complete for the
last 10 years and decreases as the time frame gets larger.
As shown in the table, elasticity decreases as the time frame gets longer into the past. This
broadly confirms the theoretical finding that health care spending is less and less sensitive to
changes in national income. However, a period of 10 years seems not to be a sufficient
reference period, given high volatility of results across countries (see standard deviation) and
high dependence of total and especially public health care spending on short and mediumterm political decisions. In this context, the figures on elasticity over the last 20 and 30 years
seem much more reliable, even if the measuring techniques were arguably less sophisticated
in the 1970s and 1980s than they are now.
A strong drawback of presented analysis is the lack of data for the New Member States. The
OECD database includes only four new Member States (CZ, HU, PL, SK), but even for them
the time series available are relatively short (5-15 years). This makes it difficult to estimate
the current value of elasticity for all EU10 countries.
Existing caveats and prospects for improvement
Arguably, the agreed methodology has limitations and the following caveats should be borne
in mind:
• ideally, projections should take into account changes in the health care status of the
population over time, looking at the prevalence of different medical conditions (which may
change over time linked to factors such as lifestyle) and the costs of treating each medical
condition (which may be affected by technological developments). While a projection
methodology looking at specific medical conditions may be feasible at a national level (see
Holly 2005), it is not a practical approach for a cross-country projection exercise given the
lack of comparable epidemiological data on the health status across EU populations in a
base year. The only comparable data that is available is essentially of a macro nature.
While lack of comparable data is a constraint for this projection exercise, the situation may
127
improve in coming years. For example, results have recently become available from the
first SHARE survey on the economic, social and health conditions for 13 countries (see
Börsch-Supan et al. 2005). SHARE is financed under the 5th Research Framework
Programme of the EU.
• health care spending is to a large extent determined by the policy decisions of national
governments, e.g. whether specific treatment are provided by public health systems, the
coverage of people eligible for public health services, the ‘quality’ of public health care
(policy choices/preferences for waiting lists, size of hospital wards, etc.). The different
institutional arrangements of health care systems across Member States imply that these
factors cannot be taken into account in projections made at a multilateral level, although
they can be included in national projections when clear policy goals/targets exist (see
Wanless 2002).
4.4.
4.4.1.
Results of the budgetary projection exercise
Pure ageing scenario
Table 4-8 presents the projection results for the pure ageing scenario under the assumption
that costs evolve in line with GDP per capita (scenario I). Public spending on health care is
projected to increase by between 1 and 2 percentage points of GDP in most Member States
between 2004 and 2050. Despite their less favourable demographic prospects, public
spending on health is projected to grow by less in the EU10 than in the EU15 countries, i.e.
on average by 0.5% of GDP. This reflects both lower initial level of spending (4.9%
compared to 6.4% of GDP in 2004) and their flatter age-related expenditure profiles.
Table 4-8 Projection results for the pure ageing scenario (I): public spending on health
care as % of GDP
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
2004
6,2
6,9
6,0
5,1
6,1
7,7
5,3
5,8
5,1
6,1
5,3
6,7
5,6
6,7
7,0
2,9
6,4
5,4
5,5
3,7
5,1
4,2
4,1
4,4
6,4
6,4
6,4
6,3
4,9
2010
6,4
7,0
6,3
5,3
6,3
8,0
5,5
6,0
5,2
6,3
5,5
6,8
5,8
6,8
7,2
3,1
6,7
5,6
5,7
3,8
5,3
4,5
4,3
4,6
6,6
6,6
6,7
6,5
5,1
2030
7,3
7,7
7,0
5,9
7,3
9,0
6,4
6,7
5,8
7,1
6,3
6,7
6,7
7,5
8,3
3,6
7,7
6,0
6,2
4,1
5,6
5,6
5,0
5,5
7,4
7,4
7,5
7,3
5,7
2050
7,7
8,0
7,3
6,9
8,3
9,5
7,3
7,2
6,2
7,4
6,9
7,3
7,0
7,8
9,3
4,0
8,3
6,3
6,5
4,4
5,9
6,2
5,4
6,1
7,8
8,1
8,2
7,9
6,1
change
2004-2050
1,5
1,1
1,3
1,8
2,2
1,8
2,0
1,4
1,1
1,3
1,7
0,6
1,5
1,0
2,3
1,1
1,9
0,9
1,0
0,7
0,7
2,0
1,3
1,8
1,4
1,7
1,7
1,6
1,2
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
128
4.4.2. Scenario on the health status
Table 4-9 presents the projection results for the constant health scenario under the assumption
that costs evolve in line with GDP per capita. It also compares the difference in projection
results with the results for the pure ageing scenario outlined on Table 4-8 above. As expected,
improved health care status will attenuate future pressure on health care spending. If one
assumes that healthy life expectancy increases at the same pace as the projected gains in total
age-specific life expectancy (constant health scenario), then the projected increase in health
care spending due to ageing (represented by pure ageing scenario) would be halved. For the
EU15 countries, public spending on health in the constant health scenario is projected to
increase by only 0.9% of GDP (0.6% in the EU10 countries) compared with 1.7% (1.2%) in
the pure ageing scenario. Most of the projected expenditure savings compared with the pure
ageing scenario appear to materialise before 2030.
Table 4-9 Projection results for constant health scenario (II)
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
2004
6,2
6,9
6,0
5,1
6,1
7,7
5,3
5,8
5,1
6,1
5,3
6,7
5,6
6,7
7,0
2,9
6,4
5,4
5,5
3,7
5,1
4,2
4,1
4,4
6,4
6,4
6,4
6,3
4,9
2010
6,2
6,8
6,1
5,3
6,1
7,8
5,3
5,8
5,1
6,2
5,3
6,7
5,6
6,7
7,0
3,0
6,6
5,5
5,5
3,8
5,3
4,4
4,2
4,5
6,6
6,4
6,5
6,4
5,0
2030
6,6
7,2
6,4
5,5
6,8
8,4
5,8
6,3
5,4
6,8
5,8
6,2
6,2
6,9
7,4
3,3
7,1
5,5
5,6
3,9
5,2
5,1
4,5
5,0
7,0
6,8
6,9
6,8
5,2
2050
6,9
7,1
6,7
6,3
7,7
8,8
6,4
6,6
5,6
6,9
6,3
6,6
6,4
7,0
7,9
3,6
7,5
5,7
5,8
4,0
5,3
5,5
4,8
5,5
7,3
7,3
7,4
7,2
5,5
Difference as % of GDP compared
to pure ageing scenario
change
2004-2050
0,7
0,3
0,6
1,2
1,6
1,1
1,1
0,8
0,5
0,8
1,0
-0,1
0,9
0,3
0,9
0,7
1,0
0,2
0,3
0,3
0,2
1,2
0,7
1,1
0,9
0,9
0,9
0,9
0,6
2010
-0,2
-0,2
-0,1
-0,1
-0,1
-0,2
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,2
-0,1
-0,1
-0,1
-0,1
0,0
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
2030
-0,6
-0,6
-0,5
-0,4
-0,5
-0,6
-0,6
-0,4
-0,4
-0,3
-0,5
-0,5
-0,5
-0,5
-0,9
-0,2
-0,7
-0,4
-0,5
-0,2
-0,4
-0,5
-0,4
-0,5
-0,4
-0,6
-0,6
-0,5
-0,5
2050
-0,8
-0,8
-0,7
-0,6
-0,6
-0,7
-0,8
-0,5
-0,6
-0,5
-0,7
-0,7
-0,6
-0,8
-1,4
-0,4
-0,9
-0,7
-0,7
-0,4
-0,5
-0,7
-0,6
-0,7
-0,5
-0,8
-0,8
-0,7
-0,6
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
4.4.3.
Death-related costs
Table 4-10 shows the budgetary projection results for the death-related costs scenario63. The
projection is made using the baseline population projection and assuming costs evolve in line
with GDP per capita. Taking death-related costs into account when projecting future health
63
To run scenario VI on death related costs, the following additional data inputs were also used (i) life
expectancy in each single year of life and gender, by single year of time over the period 2004-2050 based on
the AWG population scenario described in chapter 2.1, (ii) projections on the mortality rate for each single
year of life and gender, by single year of time over the period 2004-2050 based on the AWG population
scenario, (iii) the average expenditure per capita on health care disaggregated by 5-year age groups and by
gender (expressed in euros) as used the pure ageing scenario, (iv) GDP per capita growth over the period
2004-2050 based on in agreed underlying assumptions and reported on table 4-6 in Annex 4.
129
care spending leads to a considerable reduction of expenditure in comparison with the pure
ageing scenario over the whole projection period. Public spending on health care is projected
to increase by on average 1.3% of GDP, i.e. about 0.4 p.p. of GDP less than in pure ageing
scenario. However, the extent of projected changes varies significantly, ranging from 0.2% of
GDP in PT to an increase by 1.9% of GDP in ES). Overall, the projected change in public
spending on health care is close to projection results for the constant health scenario (II)
inspired by the dynamic equilibrium hypothesis. As in the other scenarios reflecting changes
in health status of the populations, the projected increase in spending is somewhat lower in
EU10 than EU15 countries (due to lower initial levels of spending but also to their flatter agerelated expenditure profiles described in the previous section).
Table 4-10 Projection results for the death-related costs scenario (III)
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
2004
6,2
6,9
6,0
5,1
6,1
7,7
5,3
5,8
5,1
6,1
5,3
6,7
5,6
6,7
7,0
2,9
6,4
5,4
5,5
3,7
5,1
4,2
4,1
4,4
6,4
6,4
6,4
6,3
4,9
2010
6,4
6,9
6,2
5,3
6,2
7,9
5,4
5,9
5,2
6,2
5,4
6,8
5,7
6,8
7,1
3,0
6,6
5,6
5,6
3,8
5,3
4,4
4,3
4,6
6,6
6,5
6,6
6,5
5,0
2030
6,9
7,5
6,8
5,7
7,1
8,7
6,1
6,5
5,7
6,9
6,1
6,5
6,4
7,2
8,0
3,4
7,4
5,7
5,8
4,0
5,4
5,1
4,8
5,3
7,1
7,2
7,3
7,1
5,4
2050
7,3
7,6
7,0
6,5
8,0
9,1
6,8
6,8
6,0
7,1
6,6
6,9
6,7
7,5
8,8
3,8
7,8
5,9
6,0
4,1
5,5
5,4
5,0
5,7
7,4
7,7
7,8
7,6
5,7
Difference as % of GDP compared
to pure ageing scenario
change
2004-2050
1,1
0,7
1,0
1,4
1,9
1,4
1,5
1,1
0,8
1,0
1,3
0,2
1,1
0,7
1,8
0,9
1,4
0,5
0,5
0,4
0,4
1,1
0,9
1,3
1,0
1,3
1,4
1,3
0,8
2010
0,0
-0,1
-0,1
0,0
-0,1
-0,1
-0,1
0,0
0,0
0,0
-0,1
-0,1
-0,1
0,0
-0,1
0,0
-0,1
0,0
-0,1
0,0
0,0
-0,1
0,0
0,0
-0,1
-0,1
-0,1
-0,1
-0,1
2030
-0,3
-0,3
-0,2
-0,2
-0,2
-0,3
-0,3
-0,2
-0,1
-0,2
-0,2
-0,2
-0,2
-0,2
-0,3
-0,1
-0,3
-0,2
-0,3
-0,1
-0,2
-0,4
-0,2
-0,3
-0,3
-0,2
-0,2
-0,2
-0,3
2050
-0,4
-0,4
-0,3
-0,4
-0,4
-0,4
-0,5
-0,3
-0,2
-0,3
-0,4
-0,4
-0,4
-0,3
-0,5
-0,2
-0,5
-0,4
-0,6
-0,3
-0,3
-0,8
-0,4
-0,4
-0,4
-0,4
-0,4
-0,3
-0,4
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
4.4.4.
Income elasticity of demand
As discussed in EPC and European Commission (2005b), there is strong empirical evidence
as regards the link between per capita national income and public expenditure on health care
as a share of GDP. Scenario IV is the same as the pure ageing scenario (I) in all respects
except the income elasticity of public spending is assumed to be 1.1 in the base year of 2004
and thereafter converge to 1 by the end of the projection period in 2050. As expected, higher
responsiveness of health care spending to the national income results in proportionately
higher expenditure linked to each percentage point of GDP per capita growth, even though
this effect declines as elasticity converges to 1 at the end of projection period. Given the
agreed assumptions, total spending on health care is projected to increase on average by 2.0%
of GDP, i.e. 0.3% of GDP more than in the pure ageing scenario. In nominal terms EU15 can
expect higher increase than EU10 (2.1% compared to 1.7% of GDP), but in terms of
percentage increase spending in EU10 countries is projected to marginally exceed that in
EU15.
130
Table 4-11 Projection results for scenario IV capturing a positive income elasticity of
demand for health care spending
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
2004
6,2
6,9
6,0
5,1
6,1
7,7
5,3
5,8
5,1
6,1
5,3
6,7
5,6
6,7
7,0
2,9
6,4
5,4
5,5
3,7
5,1
4,2
4,1
4,4
6,4
6,4
6,4
6,3
4,9
2010
6,5
7,1
6,3
5,4
6,3
8,1
5,6
6,0
5,4
6,3
5,5
6,9
5,8
6,9
7,3
3,1
6,8
5,8
5,8
4,0
5,6
4,6
4,4
4,7
6,8
6,7
6,7
6,6
5,2
2030
7,5
8,0
7,2
6,1
7,6
9,2
6,8
6,9
6,2
7,3
6,5
6,9
6,9
7,8
8,6
3,8
8,2
6,5
6,6
4,5
6,1
5,8
5,4
6,0
7,8
7,7
7,8
7,6
6,1
2050
8,0
8,3
7,6
7,2
8,7
9,9
7,7
7,4
6,7
7,7
7,2
7,5
7,3
8,1
9,7
4,2
8,9
6,9
6,9
4,8
6,5
6,5
5,8
6,7
8,3
8,4
8,5
8,2
6,6
Difference as % of GDP compared
to pure ageing scenario
change
2004-2050
1,8
1,4
1,6
2,1
2,6
2,2
2,4
1,6
1,5
1,6
1,9
0,8
1,8
1,4
2,7
1,3
2,4
1,5
1,4
1,1
1,4
2,2
1,7
2,3
1,9
2,0
2,1
1,9
1,7
2010
0,1
0,1
0,1
0,1
0,1
0,1
0,1
0,1
0,1
0,0
0,1
0,1
0,1
0,1
0,1
0,1
0,1
0,2
0,1
0,1
0,2
0,0
0,1
0,1
0,1
0,1
0,1
0,1
0,1
2030
0,2
0,2
0,2
0,2
0,3
0,3
0,4
0,2
0,4
0,2
0,2
0,2
0,2
0,3
0,3
0,2
0,5
0,5
0,4
0,4
0,6
0,2
0,4
0,4
0,4
0,3
0,3
0,2
0,4
2050
0,3
0,3
0,3
0,2
0,3
0,3
0,5
0,3
0,5
0,2
0,3
0,3
0,3
0,4
0,4
0,3
0,5
0,6
0,4
0,4
0,6
0,3
0,4
0,5
0,5
0,3
0,3
0,3
0,5
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
4.4.5.
Unit costs evolve in line with GDP per worker
Table 4-12 presents the results for scenario V where unit costs evolve in line with GDP per
worker. Public spending on health care is projected to increase by between 0.7 and 3.6
percentage points of GDP in most Member States between 2004 and 2050, with a noticeable
exception of LU, where spending is expected to fall. As expected, dispersion of results
appears higher than in pure ageing scenario and the projected expenditure increases are in
most countries higher when unit costs evolve in line with GDP per worker compared with
GDP per capita. For the EU25, average spending on health care is projected to increase by
2.3% of GDP by 2050 if costs evolve in line with GDP per capita compared with a projected
increase of 1.7% of GDP if costs evolve in line with GDP per worker.
131
Table 4-12 Projection results for scenario V where unit costs evolve in line with GDP per
worker
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
2004
6,2
6,9
6,0
5,1
6,1
7,7
5,3
5,8
5,1
6,1
5,3
6,7
5,6
6,7
7,0
2,9
6,4
5,4
5,5
3,7
5,1
4,2
4,1
4,4
6,4
6,4
6,4
6,3
4,9
2010
6,2
7,0
6,0
5,2
5,9
7,8
5,2
5,7
4,9
6,2
5,3
6,7
5,7
6,7
7,0
2,9
6,6
5,2
5,4
3,5
4,8
4,4
4,0
4,4
6,5
6,4
6,5
6,3
4,9
2030
7,4
8,3
7,0
6,0
7,0
9,2
6,1
6,5
5,2
7,6
6,6
6,9
7,1
7,8
8,6
3,5
7,9
5,7
6,0
3,8
5,2
5,5
4,4
5,0
8,0
7,5
7,7
7,4
5,4
2050
8,1
8,6
7,8
7,9
9,4
10,1
7,7
7,8
4,9
7,9
7,6
8,5
7,5
8,1
10,0
4,2
9,8
6,5
7,1
4,4
6,1
6,4
5,4
6,6
9,4
8,7
8,8
8,5
6,6
Difference as % of GDP compared
to pure ageing scenario
change
2004-2050
1,9
1,7
1,8
2,8
3,3
2,4
2,4
2,0
-0,2
1,8
2,4
1,8
2,0
1,4
3,0
1,3
3,4
1,1
1,6
0,7
0,9
2,2
1,3
2,2
2,9
2,3
2,4
2,2
1,7
2010
-0,2
0,0
-0,3
-0,1
-0,3
-0,2
-0,2
-0,3
-0,3
-0,1
-0,2
-0,1
-0,1
-0,1
-0,1
-0,1
-0,1
-0,4
-0,2
-0,3
-0,5
-0,1
-0,3
-0,2
-0,1
-0,2
-0,2
-0,2
-0,2
2030
0,1
0,5
0,1
0,1
-0,3
0,2
-0,3
-0,2
-0,5
0,5
0,2
0,2
0,5
0,3
0,3
0,0
0,2
-0,2
-0,1
-0,3
-0,3
-0,1
-0,6
-0,6
0,6
0,1
0,1
0,0
-0,3
2050
0,4
0,6
0,5
1,0
1,1
0,6
0,5
0,6
-1,3
0,4
0,7
1,2
0,5
0,3
0,7
0,2
1,5
0,2
0,6
0,0
0,2
0,2
0,0
0,5
1,5
0,6
0,6
0,6
0,5
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
4.4.6.
An AWG reference scenario
This scenario combines a number of elements in the scenarios described above. In particular,
in order to approximate the effect of death-related costs, it assumes the health status to
improve by half as much as in the constant health scenario. Moreover, it includes the effect of
income elasticity of health care spending converging from 1.1 in the base year to unity by
2050, while the costs are assumed to evolve following GDP per capita developments.
The results show the impact of two separate effects partially offsetting each other. In EU15
countries the reduction in spending due to health effect is expected to be somewhat larger
than extra spending due to higher income elasticity, thus average increase in expenditure
(1.6% of GDP between 2004 and 2050) is expected to be marginally lower than the level
predicted by the pure ageing scenario (1.7% of GDP). The opposite applies to the EU10
countries where income effect slightly exceeds health effect and AWG reference scenario
produces higher results than pure ageing scenario.
132
Table 4-13 Projection results for AWG reference scenario
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
2004
6,2
6,9
6,0
5,1
6,1
7,7
5,3
5,8
5,1
6,1
5,3
6,7
5,6
6,7
7,0
2,9
6,4
5,4
5,5
3,7
5,1
4,2
4,1
4,4
6,4
6,4
6,4
6,3
4,9
2010
6,4
7,0
6,3
5,4
6,3
8,0
5,5
6,0
5,3
6,3
5,5
6,8
5,8
6,8
7,2
3,1
6,8
5,8
5,7
4,0
5,5
4,5
4,4
4,7
6,7
6,6
6,7
6,5
5,2
2030
7,1
7,7
6,9
5,9
7,3
8,9
6,4
6,7
5,9
7,1
6,3
6,6
6,6
7,5
8,1
3,6
7,8
6,2
6,3
4,4
5,9
5,5
5,1
5,7
7,6
7,4
7,5
7,3
5,8
2050
7,6
7,8
7,2
6,8
8,3
9,5
7,3
7,1
6,3
7,4
6,8
7,2
7,0
7,7
8,9
4,0
8,4
6,5
6,5
4,6
6,2
6,1
5,5
6,3
8,0
7,9
8,1
7,8
6,2
Difference as % of GDP compared
to pure ageing scenario
change
2004-2050
1,4
1,0
1,2
1,7
2,2
1,8
2,0
1,3
1,2
1,3
1,6
0,5
1,4
1,0
1,9
1,1
2,0
1,1
1,0
0,9
1,1
1,8
1,4
1,9
1,6
1,6
1,6
1,5
1,3
2010
0,0
0,0
0,0
0,0
0,0
0,0
0,1
0,0
0,1
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,1
0,2
0,1
0,1
0,2
0,0
0,1
0,1
0,1
0,0
0,0
0,0
0,1
2030
-0,1
-0,1
-0,1
0,0
0,0
0,0
0,1
0,0
0,1
0,0
-0,1
-0,1
0,0
0,0
-0,2
0,1
0,1
0,3
0,1
0,2
0,4
0,0
0,1
0,2
0,2
0,0
-0,1
0,0
0,1
2050
-0,1
-0,1
-0,1
-0,1
0,0
-0,1
0,0
0,0
0,1
0,0
-0,1
-0,1
0,0
0,0
-0,4
0,1
0,1
0,2
0,0
0,2
0,3
-0,1
0,1
0,1
0,2
-0,1
-0,1
-0,1
0,1
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
4.5. Overall results of the health care projections
4.5.1.
A comparison of projection results for all approaches
Table 4-14 presents a summary of the projected change in health care spending between 2004
and 2005, expressed as a % of GDP, for all scenarios presented. To cast light on the
difference in spending projections across approaches, Table 4-15 presents the projection
results in terms of difference from scenario I. The following overall conclusions can be
drawn:
• the pure demographic effect of an ageing population is projected to push up health
care spending by between 1 and 2% of GDP in most Member States. At first sight,
this may not appear to be very large when spread over several decades. However, on
average it would amount to approximately a 25% increase in spending on health care
as a share of GDP;
• changes in the health care status of elderly citizens would have a large effect on health
spending. If healthy life expectancy (falling morbidity rates) evolve broadly in line
with change in age-specific life expectancy (similar to the dynamic equilibrium
hypothesis), then the projected increase in spending on health care due to ageing
would be halved;
• if so-called ‘death-related costs’ are taken into account, expenditure is projected to
increase significantly slower than in the pure ageing scenario as the share of people in
their final phase of life in each age cohort is getting smaller as average life expectancy
increases. At the same time, death-related costs are affected by terminal illnesses only
133
and do not reflect developments in other kinds of morbidity. Therefore, reduction in
spending is not as high as in the constant health scenario, which assumes overall
morbidity to improve in line with changes in life expectancy;
• changes in per capita income could have an important impact on health care spending,
especially if it is viewed as a luxury good. Introducing stylised effect of a 1.1 income
elasticity converging to 1 over the whole projection period increases total spending by
extra 0.3% over ‘pure demographic’ effect of ageing. This impact will arguably be
stronger in the EU10 Member States which will face a particular challenge in
balancing the demands of their citizens for wider access to health care services and for
services of similar quality to that in the rest of the EU, with their capacity to pay;
• the projection results are sensitive to the assumptions on unit costs. This can be seen
by contrasting the results where costs evolve in line with GDP per capita (scenario I)
and GDP per worker (scenario V). Contingent on the macroeconomic assumptions,
the overall spending on health care calculated with GDP per worker may be twice as
much as expenditure calculated using GDP per capita in some countries, and about the
same in the others;
• compared with the 2001 projection exercise, the most significant progress relates to
the inclusion of scenarios dealing with the health care status of the elderly and deathrelated costs. This progress is broadly reflected in the choice of AWG reference
scenario which includes demographic changes, health status and national income as
the factors driving health care spending in the decades to come. Caution should be
exercised, however, as there is not conclusive evidence that the ‘positive’ trends will
occur nor of the scale of their likely impact. Overall, more progress has been made in
extending the projection methodology for health care on factors that tend to lower
health care spending than on driving forces that could potentially increase spending.
Less progress, however, has been made in incorporating other non-demographic
factors into the projection exercise (some tentative results are presented in the annex
6). In particular, the possible impact of technology on health care spending warrants
further analysis.
134
Table 4-14 Overview of projected changes in health care spending as a % of GDP
between 2004 and 2050
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
Pure ageing
GDP per
capita
1,5
1,1
1,3
1,8
2,2
1,8
2,0
1,4
1,1
1,3
1,7
0,6
1,5
1,0
2,3
1,1
1,9
0,9
1,0
0,7
0,7
2,0
1,3
1,8
1,4
1,7
1,7
1,6
1,2
Constant
health
0,7
0,3
0,6
1,2
1,6
1,1
1,1
0,8
0,5
0,8
1,0
-0,1
0,9
0,3
0,9
0,7
1,0
0,2
0,3
0,3
0,2
1,2
0,7
1,1
0,9
0,9
0,9
0,9
0,6
Death-related
costs
1,1
0,7
1,0
1,4
1,9
1,4
1,5
1,1
0,8
1,0
1,3
0,2
1,1
0,7
1,8
0,9
1,4
0,5
0,5
0,4
0,4
1,1
0,9
1,3
1,0
1,3
1,4
1,3
0,8
Income
elasticity
1,8
1,4
1,6
2,1
2,6
2,2
2,4
1,6
1,5
1,6
1,9
0,8
1,8
1,4
2,7
1,3
2,4
1,5
1,4
1,1
1,4
2,2
1,7
2,3
1,9
2,0
2,1
1,9
1,7
Unit costs GDP per
worker
1,9
1,7
1,8
2,8
3,3
2,4
2,4
2,0
-0,2
1,8
2,4
1,8
2,0
1,4
3,0
1,3
3,4
1,1
1,6
0,7
0,9
2,2
1,3
2,2
2,9
2,3
2,4
2,2
1,7
AWG
reference
scenario
1,4
1,0
1,2
1,7
2,2
1,8
2,0
1,3
1,2
1,3
1,6
0,5
1,4
1,0
1,9
1,1
2,0
1,1
1,0
0,9
1,1
1,8
1,4
1,9
1,6
1,6
1,6
1,5
1,3
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
Table 4-15 Difference in the projected changes in health care spending 2004-2050
between Scenario I (pure ageing, costs evolve in line with GDP per capita, using national
age-related expenditure profiles) and the other scenarios
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU12
EU10
Pure ageing
GDP per
capita
1,5
1,1
1,3
1,8
2,2
1,8
2,0
1,4
1,1
1,3
1,7
0,6
1,5
1,0
2,3
1,1
1,9
0,9
1,0
0,7
0,7
2,0
1,3
1,8
1,4
1,7
1,7
1,6
1,2
Constant
health
-0,8
-0,8
-0,7
-0,6
-0,6
-0,7
-0,8
-0,5
-0,6
-0,5
-0,7
-0,7
-0,6
-0,8
-1,4
-0,4
-0,9
-0,7
-0,7
-0,4
-0,5
-0,7
-0,6
-0,7
-0,5
-0,8
-0,8
-0,7
-0,6
Death-related
costs
-0,4
-0,4
-0,3
-0,4
-0,4
-0,4
-0,5
-0,3
-0,2
-0,3
-0,4
-0,4
-0,4
-0,3
-0,5
-0,2
-0,5
-0,4
-0,6
-0,3
-0,3
-0,8
-0,4
-0,4
-0,4
-0,4
-0,4
-0,3
-0,4
Income
elasticity
0,3
0,3
0,3
0,2
0,3
0,3
0,5
0,3
0,5
0,2
0,3
0,3
0,3
0,4
0,4
0,3
0,5
0,6
0,4
0,4
0,6
0,3
0,4
0,5
0,5
0,3
0,3
0,3
0,5
Unit costs GDP per
worker
0,4
0,6
0,5
1,0
1,1
0,6
0,5
0,6
-1,3
0,4
0,7
1,2
0,5
0,3
0,7
0,2
1,5
0,2
0,6
0,0
0,2
0,2
0,0
0,5
1,5
0,6
0,6
0,6
0,5
AWG
reference
scenario
-0,1
-0,1
-0,1
-0,1
0,0
-0,1
0,0
0,0
0,1
0,0
-0,1
-0,1
0,0
0,0
-0,4
0,1
0,1
0,2
0,0
0,2
0,3
-0,1
0,1
0,1
0,2
-0,1
-0,1
-0,1
0,1
Note: EU25, EU15, EU12 and EU10 – average weighted by GDP
135
4.5.2.
Tentative conclusions
First, governments in all EU countries are heavily involved in the financing and/or provision
of health care services, and universal access is virtually assured in all countries. There is,
nevertheless, a wide variety of institutional arrangements, making it very difficult to draw
general conclusions on detailed factors and policies driving expenditures. What is apparent,
however, is that
• increases in spending on health care as a share of GDP in past decades have not been
strongly influenced by demographic developments, but rather by policy decisions to
enlarge access, by the demand for better quality health care linked to growing income
levels, and (albeit less conclusively) by technology (as falls in unit costs to date appear to
have been more than offset by increased demand and quality improvements);
• there are very big differences across Member States in terms of per capita spending on
and inputs to health care systems, which do not appear to be correlated with health care
outcomes. A priori, this suggests there is considerable scope for efficiency gains. It is
difficult to draw conclusions as to whether and how institutional design affects health care
outcomes or efficiency.
Second, the demand for health care (and social care) depends ultimately on the health status
and functional ability of (elderly) citizens, and not on age per se. Even if age is not the causal
factor, ageing populations may lead to pressure for higher public spending on health care.
This will result from the very large projected increase (70% for persons aged 65+, and 170%
for persons aged 85+ in EU25) in older cohorts with a higher prevalence of medical
conditions, sometimes chronic, that require (expensive) health care services.
Third, ageing is only one of several factors driving health care spending, and other nondemographic determinants are likely to be of equal significance in determining future
spending levels. On balance, overall public spending looks set to increase in the context of an
ageing society. However, there are upside and downside risks (possibly substantial) to the
projected increase in public spending on health care based on a pure ageing scenario. In
particular, the different approaches to projecting health care spending underline the critical
role played by
• the health status of the population. The projections illustrate that if most of the future
gains in life expectancy are spent in broadly good health and free of disability, this could
offset up to one half of the projected increases in spending due to an ageing population (the
pure ageing scenario). It should, however, be stressed that the current projections are not
modelled on the basis of a direct indicator of morbidity, but rather on the basis of stylised
assumptions. This is a shortcoming as morbidity patterns change over time (multi- and
chronic diseases such as cardiovascular problems now outweigh infectious diseases) and
an ageing society may possibly lead to new patterns of morbidity and mortality. For
example, the increase in the share of persons surviving to very old ages (80+) may lead to
an increase in the prevalence of chronic and degenerative diseases (e.g. neuro-degenerative
and musculoskeletal diseases);
• relative cost developments in the health care. The projection results show that spending
levels are sensitive to the assumptions on evolution of unit costs in the health care sector.
Leaving aside demographic factors, spending on health as a share of GDP could change as
a result of several factors, e.g. unit costs (wages, pharmaceutical prices) growing faster
136
than their equivalents in the economy as a whole, public policies to improve access to
health or improve quality (reduce waiting lists, increase choice), rising income levels and
the impact of technology on total health care spending. The current set of projections is not
capable of disentangling the contribution of each factor, which suggests a possible avenue
for future work;
• the effective incorporation of technology into health care system. Technology could either
increase or decrease overall public spending on health depending on whether the savings
from more effective medical treatments and lower unit costs outweigh the additional
spending resulting from the opening up of new and more affordable services.
Fourth, ageing will not only raise a policy challenge in terms of putting pressure for increased
spending on health care. Of equal, if not more relevance, is the impact of ageing on the type
of health care services that will be needed. As argued above (and in the literature), morbidity
and mortality patterns are changing in the context of an ageing society, and a key challenge
for health care systems is to adapt accordingly. There may be a need to rebalance the various
types of care (primary and secondary, outpatient and hospital care, classical health care, longterm care and social care).
Fifth, while the current set of projection do not model the institutional arrangements for the
provision of health care services within Member States, the projection results may
nonetheless provide several useful policy insights as follows:
• as outlined above, changing morbidity patterns and ‘healthy life expectancy’ will be of
critical importance. What is striking from the review of existing literature is the lack of
comparable data and evidence and analysis within Europe on this matter. A heavy
reliance is therefore placed on data and analysis from third countries, notably the US,
which may only be of partial relevance for the EU, given possible differences in morbidity
patterns and also the very different organisational arrangements of the health care sector.
The situation as regards data is improving with the recent release of the SHARE survey.
However, more investment is required, especially in longitudinal surveys, in order to get a
more accurate and comparable picture on the evolution of health care trends of the
European population over time;
• past improvements in life expectancy (and healthy life expectancy) are attributable to a
variety of factors including better public health systems, improved education, changes in
nutrition and lifestyle. Understanding the precise role which public policies play in shaping
health care outcomes is of critical importance. Effective preventive actions to tackle
obesity, smoking and drug abuse could have large effects on the health care status of
citizens, and thus on future spending needs. However the evidence of the effectiveness of
preventive schemes is mixed and warrants further analysis.
Sixth, the prospect of increased spending on health care in an ageing society will be a cause
for concern for Finance Ministers as it will make the tasks of achieving and sustaining
sound budget positions more challenging. However, the policy challenge needs to be viewed
in terms of general welfare and not budgetary considerations alone, bearing in mind the
equally important goals of access and adequacy of health care systems. A priori, there is no
economic reasons why countries should not devote a larger share of resources to health care.
Increased government intervention can be justified if the income elasticity of demand is such
that demand outpaces income growth, and also if investment in technology is more than
137
compensated by improved quality and/or productivity. Notwithstanding these caveats, simply
spending more money is not an option, and difficult choices on priorities will have to be
made. The management and control of health care spending will be a critical part of overall
efforts to ensure sustainable overall public finance positions. In this regard,
• aggregate cost-containment measures to control volume, prices and wages, as well as
budgetary caps, have helped constrain expenditure especially in the hospital sector, and
are likely to remain key elements in comprehensive health care strategies of Member
States. However, their effectiveness may diminish over time as suppliers alter their
behaviour and they risk introducing distortions that could lead to costly inefficiencies.
Shifting some of the costs to the private sector, for example via cost-sharing requirements,
can also help to control public expenditures: however, the expected saving may be modest
given the need to pursue public policy objectives related to access and equity;
• efforts to improve the cost efficiency will play an increasingly important role in controlling
expenditures over the long-run. However, it is difficult to draw general conclusions on the
effectiveness of different types of cost efficiency measures, as much depends on the
institutional structure of the health care system concerned. Governments face a
considerable challenge in designing reforms that achieve a better alignment of the
economic incentives facing health care providers and users that encourage rational
resource use, in part linked to lack of data and information.
138
5.
LONG-TERM CARE
5.1.
Introduction
Some limitations with the 2001 projection exercise
The number of people aged 80 and above in the EU is projected to treble until 2050. As their
share in the population increases over the next decades, an increase in the ratio of long-term
care expenditure to GDP is expected in the future in all EU Member States. The mandate
from the ECOFIN Council to the EPC included a request to make projections for public
spending on long-term care. This followed the 2001 projection exercise which examined the
impact of demographic variables on long-term care in ten EU15 countries. The methodology
used in 2001 was a “pure” demographic scenario which only considered the impact of
changes in the size and age-structure of the population on long-term care spending. It
consisted of applying profiles of average long-term care expenditure per capita by age and
gender (provided for a base year by Member States) to a population projection of Eurostat.
The projections were run under the assumption of constant age and gender-contingent
consumption of long-term care over time. Projections were run under two cost assumptions,
i.e. expenditures per capita grow at the same rate as GDP per capita (which can be considered
as neutral in macroeconomic terms), and expenditures per capita increase at the same rate as
GDP per worker (to reflect the labour intensity of the long-term care sector).
The 2001 report of the EPC recognised the limitations of this projection methodology, in
particular the strong assumption of holding age-related expenditure profiles constant over
time. In particular, it was recognised that:
• holding the age-specific spending on long-term care constant over the projection period at
the level in a base year (usually 2000) implied that a large share of the projected gains in
life expectancy would be spent in poor health with a high degree of disability: in the
literature, this is referred to as the “expansion of morbidity/disability” hypothesis.
However, the literature points to other potential scenarios, including a “dynamic
equilibrium” hypothesis (nearly all gains in life expectancy are spent in good health and
without disability) and a “compression of morbidity/disability” hypothesis (gains in
healthy/disability-free life expectancy exceed the gains in life expectancy);64
• the 2001 projection only included scenarios on the basis of current institutional
arrangements for the provision and financing of long-term care by the public sector, i.e. a
“no policy change” scenario. This approach is an appropriate starting point for making
long-run projections. However, it could usefully be complemented with additional
scenarios to assess the impact of possible future policy changes. Pressure for more public
provision/financing of long-term care services could grow substantially in coming decades
due to changes in family structure and the growing attachment of women to the labour
market, trends which may constrain the supply of informal care provision within
households;
64
See chapter 4 on health care for a discussion of changes in the health status of the population as life
expectancy increases.
139
• the 2001 projection methodology implicitly assumed that the balance between care
provided in institutional and home-based settings remained unchanged over the projection
period. As above, this is a reasonable starting point, but it would be useful to complement
this with additional policy scenarios as unit costs may differ substantially between the two
settings.
A methodology based on the projected need for long-term care services and allowing the
exploration of different policy settings
A substantially different projection methodology has been employed in this projection
exercise. DG ECFIN has built a simple macro simulation or cell-based model, based on a
proposal by Comas-Herrera et al., (2005) and similar to those used for Germany, Italy and
Spain in the European Study of Long-Term Care Expenditure (Comas-Herrera and
Wittenberg, 2003 and Comas-Herrera et al, 2003). That project in turn built on the experience
of constructing the Personal Social Services Research Unit (PSSRU) Long Term Care
expenditure model for England (Wittenberg et al., 1998 and 2001).
The approach aims to maximise the number of factors affecting future long-term care
expenditure that can be examined, while making sure that the projections can be carried out
using mostly macro-level data so as to ensure that a large number of Member States can be
included in the projections. Specifically, the methodology aims at analysing the impact of
changes in the assumptions made about:
• the future numbers of elderly people (through changes in the population projections used);
• the future numbers of dependent elderly people (by making changes to the prevalence rates
of dependency);
• the balance between formal and informal care provision;
• the balance between home (domiciliary) care and institutional care within the formal care
system;
• the costs of a unit of care.
140
5.2.
The projection methodology and scenarios
5.2.1.
Overview of the projection model
Graph 5-1 provides an overview of the model structure. The square boxes indicate data that
need to be entered into the model to make projections for each year, and the round boxes
indicate calculations that are produced within the model for each year.
Graph 5-1
Model structure
1. Population by
age and gender
2. Dependency rates
by age and gender,
base & future
developments
Nondependent
population
Dependent
population
3. Probability of receiving types of
long-term care, by age and gender.
Informal
care only
5. Proportion of
dependent people
receiving disabilityrelated benefits
Formal care at
home
4. Average public exp formal care
at home per user by age per year
Formal care
institutions
4. Average public exp institutional care
per user by age per year
6. Inflation assumption
Expenditure on
disabilityrelated benefits
Expenditure on
formal care at
home
Expenditure on
institutional
care
Total Public
Expenditure on
Long-Term Care
141
Step 1: taking the baseline population projection (by age and gender), a projection is made of
the dependent population, who are assumed to need some form of long-term care service, and
the non-dependent population who are assumed not to be in need of long-term care services.
This is made by extrapolating age and gender-specific dependency ratios of a base year
(estimated using existing indicators of disability from comparable sources) to the baseline
population projection. It is worth stressing at this point the difference between the terms
“dependency” and “disability”. The term “disability” refers to some functional impairment of
an individual. The term “dependent” refers to the share of the population having some
disability which requires the provision of a care service. There are many people with some
form of disability who can lead completely independent lives without the need for care
services. More specifically, this note makes use of the concept of ADL-dependency which
refers to difficulties in performing at least one Activity of Daily Living (ADL) (Katz et al.,
1963).
Step 2 is to split, by age and gender, the dependent elderly population into three groups
depending on the type of care they receive, namely (i) informal care, which has no impact on
public spending, (ii) formal care at home and (iii) formal care in institutions (both of which
impact on public spending but their unit costs may differ). The model implicitly assumes that
all those receiving home care or institutional care have difficulties with one or more ADLs,
and that all persons deemed ADL-dependent either receive informal care, home care or
institutional care. The split by type of care received is made by calculating the “probability of
receiving different types of long-term care by age and gender”. This is calculated for a base
year using data on the numbers of people with dependency (projected in step 1), and the
numbers of people receiving formal care at home and in institutions (provided by Member
States). It is assumed that the difference between the total number of dependent people and
the total number of people receiving formal care (at home or in institutions) is the number of
people who rely exclusively on informal care.
Step 3 involves the calculation of public spending for the two types of long-term care service,
by multiplying the number of people receiving long-term care services (at home and in
institutions) by the average age-specific public expenditure of formal care (at home and in
institutions) per year and per user. Average expenditure is calculated for a base year using
data on total public expenditure in home care and institutional care and the numbers of people
receiving formal care at home and in long-term care institutions (provided by Member States).
Two assumptions are required:
•
it is implicitly assumed that current expenditure in services divided by the number of
users equals the long-run unit costs of services;
•
it is assumed that average expenditure per user increases with the age of the user.65
Step 4: by adding up the expenditure on formal care at home and in institutions, total public
expenditure on long-term care services is obtained. Public expenditure on cash benefits for
people with ADL-dependency is then added to the expenditure on services, in order to obtain
65
In practice, average expenditure (aged 65 and above), for each type of service, is decomposed into average
expenditure by age groups, by assuming the same rate of increase in spending by age as in the age-related
expenditure profile. It is important to note that the age-related expenditure profile provides information on
spending in formal care by age, without distinction between care provided at home and in institutions. The
model uses average public expenditure in formal care and in institutional care to project future expenditure
in both types of services.
142
total public expenditure on long-term care; note that cash benefits are assumed to grow in line
with the numbers of people with dependency and also with the age of the user.
Overall, given the availability of a numerical measure of disability, the projection
methodology described above is more precise than that used in chapter 4 on health care where
there is no direct indicator of health status and the age-related expenditure profile is used as a
proxy. However, an important caveat to note is that while dependency rates are an indicator of
the need for care, those needs may not necessarily translate into actual public expenditure, as
most long-term care is provided by unpaid informal carers. Expenditure profiles contain
information about the propensity to receive paid formal care, which depends on a number of
factors other than dependency that affect demand for paid care such as household type,
availability of informal carers, income or housing situation (Wittenberg et al, 1998). Most of
these factors, in turn, are also correlated with age.
5.2.2.
Scenarios carried out in the projection exercise
The advantage of the methodology described above is that it allows one to examine different
scenarios regarding the evolution of dependency rates, unit costs and policy settings. Table
5-1 below outlines the scenarios carried out as part of the projection exercise.
Table 5-1 Overview of scenarios
Constant
disability
scenario
Increase in
formal care
provision
AWG reference
scenario
I
Unit costs
evolve in line
with GDP per
capita
II
III
IV
V
Population
projection
AWG scenario baseline
AWG scenario baseline
AWG scenario baseline
AWG scenario baseline
AWG scenario baseline
Disability status
over time
Disability rates
held constant at
2004 level
Disability rates
held constant at
2004 level
Age-specific
disability rates
evolve in line
with changes in
age-specific
mortality rates
Disability rates
held constant at
2004 level
Policy setting
Probability of
receiving care
held constant at
2004 level
Probability of
receiving care
held constant at
2004 level
Unit costs
GDP per worker
GDP per worker
GDP per worker
Pure ageing
scenario
GDP per capita
Intermediate
between pure
ageing and
constant health
scenarios,
whereby agespecific disability
rates decrease by
half of the
decrease in agespecific mortality
rates
Probability of
Probability of 1% p.a. decrease
receiving care
receiving care
in number of
held constant at persons receiving held constant at
2004 level
2004 level
informal care up
to 2020, half
going to
institutions, half
to home care
GDP per worker
143
•
A ‘pure ageing scenario’ (column I in Table 5-1) involves keeping the proportion of
the older disabled population who receive either informal care, formal at home or
institutional care constant and applying them to the projected dependent population. It
also assumes that prevalence of ADL-dependency is unchanged over the projection
horizon, i.e. the rates used in future years are the same as those in the base year. This
implies that almost all gains in life expectancy are spent in bad health/with disability.
Arguably, it is a pessimistic scenario with respect to disability status, since it assumes
that average lifetime consumption of long-term care services will increase over time.
It is a “no policy change scenario” as the probability of receiving care (either at home
or in an institution) is assumed to remain constant at the 2004 level. This scenario is
based on the same approach as that used in the 2001 projection exercise of the EPC.
•
A ‘unit costs scenario’ (column II) is identical to the pure ageing scenario, except that
costs are assumed to evolve in line with GDP per capita.
•
A ‘constant disability scenario’ (column III in Table 5-1) is run to reflect an
alternative assumption about trends in age-specific ADL-dependency rates. There is
substantial debate about the extent to which, gains in life expectancy will be spent free
of disability (Robine and Michel, 2004). Trends in ADL-dependency rates have
decreased in the United States (Crimmins, 2004), but the evidence for European
countries and other developed countries, such as Australia, is more mixed. Robine and
Michel (2004) conclude that the available evidence does not point to a single forecast
of expansion or compression of morbidity, but to a series of transitional stages that
could drive the trends encountered in different countries and at different times. In the
‘constant disability scenario’, which is inspired by the dynamic equilibrium
hypothesis, disability rates evolve exactly in line with age-specific mortality rates.
This is equivalent to the approach followed in chapter 4 on health care.
•
A policy change scenario is run to examine the impact of ‘an increase in the
prevalence of receiving formal care’ (column IV). This scenario examines the impact
of an increase of 1% a year in the proportion of dependent elderly people receiving
formal care, for the period 2004-2020, with the additional people receiving care in
institutions and at home in the same ratio as observed in the base year of 2004.
•
An ‘AWG reference scenario” (column V in Table 5-1) is a prudent scenario that aims
to bring together several different drivers of long-term care spending. It assumes that
age-specific disability rates fall by half of the projected decrease in age-specific
mortality rates. This implies that some half of projected gains in life expectancy up to
2050 would be spent in good health and free of disability. Note that that the aim is to
facilitate the comparison of budgetary projections across expenditure items, and thus it
should be symmetrical with the “AWG reference scenario” for health care.
5.3.
Data availability and quality
In order to run the projections, a wide variety of data is required. Table 5-2 provides an
overview of all the data inputs. It indicates which data has been supplied by Member States
(shaded) and which data is only available on the basis of average estimates (blank).
144
On the basis of available data, it is possible to make projections for 18 countries66, namely
Belgium, Denmark, Germany, Spain, Ireland, Italy, Luxemburg, the Netherlands, Finland,
Sweden, the UK, the Czech Republic, Lithuania, Latvia, Malta, Poland, Slovakia and
Slovenia. A key difficulty is that while many countries have supplied some data sets, very few
have done so for all data sets and in practice, it proved extremely difficult to collect a
complete set of the data required for many countries. Therefore, for most of these countries, it
was necessary to use estimates based on EU averages for one or two variables. Table 7-1 in
the Annex provides a detailed description of the data used.
Table 5-2 Overview of data availability
Age profile
Disability rate
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
Total number of people
in institutions
home care
cash benefits
Age breakdown of population
in institutions home care
cash benefits
estimated
estimated
estimated
estimated
in institutions
Total spending
home care
cash benefits
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
estimated
5.3.1.
estimated
Age-related expenditure profiles
Fifteen Member States have provided age-related expenditure profiles, namely Belgium,
Denmark, Germany, Italy, Luxemburg, the Netherlands, Finland, Sweden, the UK, the Czech
Republic, Lithuania, Latvia, Malta, Poland and Slovenia. A summary of key characteristics
for specific age cohorts is presented on Table 5-3 for males and Table 5-4 for females.
Graph 5-2 to Graph 5-9 display the age-related expenditure profiles, both as % of GDP per
capita and in nominal euros, grouped into EU15 and EU10 countries. The data are not
comparable as regards coverage, breakdown by age cohort and the year when the data was
collected and thus DG ECFIN has made a number of technical adjustments to arrive at a
standardised format. The main features of the age-related expenditure profiles can be
summarised as follows:
• in most countries, the age-related expenditure profile is steep, more so than for health care.
This is explained by the fact that the prevalence of frailty and disability increases
significantly with age, especially amongst the very old age cohorts. Sweden appears to be
an exception with relatively high levels of spending at younger age cohorts;
• expressed as % of GDP per capita, spending on long-term care is usually substantially
higher than for health care;
66
Austria provided data on cash-benefits, but as the data on care at home and in institutions is not available,
the results of the projection have not been included in the report.
145
• there is a huge variation in spending across countries, both in nominal terms and as a % of
GDP per capita. There is a striking gap between the EU10 and E15. For example, EU10
countries on average spend €103 on long-term care for females aged 90-94 (equivalent to
2.5% of per capita GDP) which contrasts with €12443 for EU15 countries (equivalent to
41.3% of per capita GDP). However, within EU15 countries, there is enormous variation:
spending ranges from €4764 (20.4% of per capita GDP) for people aged 90 to 94 years in
Italy to €22336 (62% of per capita GDP) in Denmark;
• spending on females is in general higher than for males of the same age-cohort. In some
cases, the differences can be large. For example, spending on males aged 90-94 amounts
on average to €10526 in the EU15 compared with €12443 for females. In the EU10, the
difference is more marked, €20 for males and €103 for females.
146
Table 5-3 Age-related expenditure profiles for long-term care, in euros and GDP per
capita – males
BE
DK
DE
IT
LU
NL
FI
SE
UK
CZ
LV
LT
MT
PL
SI
EU15 average*
cohort aged 60-64
level in
level in %
nominal
of per
euros
capita GDP
120
0.4
975
2.7
115
0.4
268
1.1
66
0.1
464
1.6
240
0.8
469
1.5
566
2.0
20
0.2
35
0.7
36
0.7
5.5
0.1
5
0.1
114
1
365
1.0
cohort aged 70-74
level in
level in %
nominal
of per
euros
capita GDP
288
1.1
2265
6.3
381
1.4
494
2.1
778
1.4
1485
5.2
961
3.3
960
3.0
752
2.6
57
0.7
55
1.2
51
1.0
22.7
0.2
9
0.2
312
2
929
2.9
cohort aged 80-84
level in
level in %
nominal
of per
euros
capita GDP
1019
3.7
8806
24.4
1690
6.4
1606
6.9
3022
5
6577
23.0
3484
12.1
9593
29.7
2604
9.1
182
2.2
63
1.3
87
1.7
2.0
2.0
16
0.3
928
7
4267
13.4
cohort aged 90-94
level in
level in %
nominal
of per
euros
capita GDP
3430
12.6
15080
41.8
5921
22.4
3045
13.0
12575
22.2
19658
68.7
11597
40.4
19867
62
5610
19.6
120
179
2.0
26
916
10754
2.5
3.4
2.0
0.5
7
33.6
20.7
standard deviation
289
0.6
618
1.8
3231
9.7
6595
EU10 average*
36
0.4
84.3
0.9
213.0
2.4
248.6
3.1
standard deviation
40
0.4
113.1
0.8
356.2
2.4
380
2.5
* unweighted average of the available figures
Source: National data
Table 5-4 Age-related expenditure profiles for long-term care in euros and GDP per
capita – females
BE
DK
DE
IT
LU
NL
FI
SE
UK
CZ
LV
LT
MT
PL
SI
EU15 average*
cohort aged 60-64
level in
level in %
nominal
of per
euros
capita GDP
119
0.4
1149
3.2
115
0.4
255
1.1
261
0.5
464
1.6
245
0.9
469
1.5
566
2.0
15
0.2
22
0.5
19
0.4
5.5
0.1
3
0.1
91
0.7
405
1.3
cohort aged 70-74
level in
level in %
nominal
of per
euros
capita GDP
391
1.4
3187
8.8
381
1.4
603
2.6
917
1.6
1485
5.2
1034
3.6
960
3.0
752
2.6
74
0.9
29
0.6
40
0.8
22.7
0.2
9
0.2
313
2.4
1079
3.4
cohort aged 80-84
level in
level in %
nominal
of per
euros
capita GDP
1835
6.7
13324
36.9
1690
6.4
2676
11.5
5618
9.9
6577
23.0
5106
17.8
9593
29.7
2604
9.1
305
3.6
75
1.6
141
2.7
2.0
2.0
28
0.6
1494
11.5
5447
16.8
cohort aged 90-94
level in
level in %
nominal
of per
euros
capita GDP
5667
20.8
22336
61.9
5921
22.4
4764
20.4
18125
31.9
19658
68.7
15719
54.8
19867
62
5610
19.6
:
:
135
2.9
219
4.2
2.0
2.0
57
1.1
1482
11.4
13074
40.2
standard deviation
320
0.9
862
2.4
3930
10.9
7404
EU10 average*
26
0.3
81
0.8
341
3.7
379
4.3
standard deviation
33
0.3
115
0.8
575
4.0
622
4.1
*
21.0
unweighted average of the available figures
Source: National data
147
Graph 5-2 Age-related expenditure profiles for longterm care, % of GDP per capita, males, 2004
Graph 5-3 Age-related expenditure profiles
for long-term care in Euros, males, 2004
25000
100
90
20000
80
70
15000
60
50
10000
40
30
5000
20
10
DK
DE
IT
NL
FI
SE
UK
BE
LU
Graph 5-4 Age-related expenditure profiles for longterm care, % of GDP per capita, females, 2004
DK
IT
NL
FI
SE
95
-9
9
90
-9
4
85
-8
9
80
-8
4
75
-7
9
70
-7
4
65
-6
9
60
-6
4
55
-5
9
45
-4
9
50
-5
4
DE
UK
Graph 5-5 Age-related expenditure profiles
for long-term care in Euros, females, 2004
100
45000
90
40000
80
35
-3
9
40
-4
4
25
-2
9
30
-3
4
014
15
-1
9
014
15
-1
9
20
-2
4
25
-2
9
30
-3
4
35
-3
9
40
-4
4
45
-4
9
50
-5
4
55
-5
9
60
-6
4
65
-6
9
70
-7
4
75
-7
9
80
-8
4
85
-8
9
90
-9
4
95
-9
9
10
0+
BE
20
-2
4
0
0
35000
70
30000
60
25000
50
20000
40
15000
30
10000
10
5000
0
0
BE
DK
DE
IT
NL
FI
SE
UK
014
15
-1
9
20
-2
4
25
-2
9
30
-3
4
35
-3
9
40
-4
4
45
-4
9
50
-5
4
55
-5
9
60
-6
4
65
-6
9
70
-7
4
75
-7
9
80
-8
4
85
-8
9
90
-9
4
95
-9
9
10
0+
014
15
-1
9
20
-2
4
25
-2
9
30
-3
4
35
-3
9
40
-4
4
45
-4
9
50
-5
4
55
-5
9
60
-6
4
65
-6
9
70
-7
4
75
-7
9
80
-8
4
85
-8
9
90
-9
4
95
-9
9
10
0+
20
LU
BE
Graph 5-6 Age-related expenditure profiles for longterm care, % of GDP per capita, males, 2004
DK
DE
IT
NL
FI
SE
UK
Graph 5-7 Age-related expenditure profiles
for long-term care in Euros, males, 2004
1000
12
900
10
800
700
8
600
500
6
400
4
300
200
2
100
LT
LV
PL
MT
95
+
90
-9
4
85
-8
9
75
-7
9
80
-8
4
70
-7
4
60
-6
4
65
-6
9
55
-5
9
50
-5
4
40
-4
4
45
-4
9
35
-3
9
25
-2
9
30
-3
4
20
-2
4
00
-1
4
15
-1
9
CZ
00
-1
4
15
-1
9
20
-2
4
25
-2
9
30
-3
4
35
-3
9
40
-4
4
45
-4
9
50
-5
4
55
-5
9
60
-6
4
65
-6
9
70
-7
4
75
-7
9
80
-8
4
85
-8
9
90
-9
4
95
-9
9
10
0+
0
0
CZ
SI
Graph 5-8 Age-related expenditure profiles for longterm care, % of GDP per capita, females, 2004
LT
LV
PL
MT
SI
Graph 5-9 Age-related expenditure profiles
for long-term care in Euros, females, 2004
1600
14
1400
12
1200
10
1000
8
800
6
600
4
400
200
2
4
9
4
9
4
9
4
9
9
4
4
4
9
9
4
4
9
-1 5-1 0-2 5-2 0-3 5-3 0-4 5-4 0-5 5-5 0-6 5-6 0-7 5-7 0-8 5-8 0-9
00
1
2
2
3
3
4
4
6
5
5
6
8
9
7
8
7
CZ
LT
LV
PL
MT
+
95
00
-1
4
15
-1
9
20
-2
4
25
-2
9
30
-3
4
35
-3
9
40
-4
4
45
-4
9
50
-5
4
55
-5
9
60
-6
4
65
-6
9
70
-7
4
75
-7
9
80
-8
4
85
-8
9
90
-9
4
95
-9
9
10
0+
0
0
CZ
LT
LV
PL
MT
SI
SI
Source: National data
148
To make projections for Spain, Ireland and Slovakia where no age-related expenditure
profiles are available, an ‘average’ profile was used, calculated as the unweighted average of
per capita expenditure expressed as % of GDP per capita. The figures are reported on Table
5-3 and Table 5-4. Two separate profiles were established for EU10 and EU15, as the shape
of the curve differs clearly between EU10 and EU15 Member States.
5.3.2.
ADL-dependent population
The comparability of ADL-dependency rates is an important issue, especially when scenarios
that involve shifting dependent elderly people between alternative care options as a result of
changing patterns of care are investigated. The European Study of Long-Term Care showed
that the impact on expenditure of some of the investigated scenarios about informal care and
changes to formal care entitlement was affected by the differences in the definitions of
dependency used in each country (see Pickard, 2003a and 2003b). With regard to dependency
rates, Eurostat reviews of the data available on ADL-related dependency in European
countries (Grammenos, 2003 and Eurostat, 2003) showed that there is a very low level of
comparability of the data collected in national surveys. However, comparable data on ADLdependency rates has recently become available for the 10 EU countries participating in the
SHARE survey on the economic, social and health conditions67, see Table 5-5.
The SHARE data results show that:
• while the levels of ADL-dependency differ across countries, a common pattern can be
discerned. Dependency rates rise with age. Based on an average of results, they increase
for males from 7.1% when they are aged 65-70 to 27.7% when they are aged 80+;
• they are generally, though not always, higher amongst females than males.
Table 5-5 Dependency rates among elderly population in households, by age
group
DK
DE
GR
ES
FR
IT
NL
AT
SE
UK
average
standard deviation
Men
0.095
0.075
0.007
0.065
0.058
0.072
0.061
0.059
0.045
0.176
0.071
0.04
65-70
Women
0.125
0.065
0.091
0.07
0.089
0.068
0.06
0.105
0.061
0.202
0.094
0.04
Men
0.056
0.069
0.006
0.112
0.172
0.098
0.04
0.077
0.088
0.239
0.096
0.07
70-74
Women
0.095
0.163
0.119
0.126
0.143
0.191
0.088
0.125
0.071
0.253
0.137
0.05
75-79
Men
Women
0.143
0.105
0.141
0.205
0.103
0.238
0.152
0.181
0.335
0.157
0.203
0.228
0.095
0.115
0.19
0.152
0.107
0.171
0.27
0.306
0.174
0.186
0.08
0.06
Men
0.333
0.332
0.241
0.296
0.306
0.31
0.189
0.133
0.256
0.37
0.277
0.07
80+
Women
0.31
0.314
0.341
0.458
0.367
0.342
0.359
0.324
0.373
0.441
0.363
0.05
Source: SHARE, 1+ ADLs
67
See Börsch-Supan et al., 2005 and http://www.share-project.org/ The following countries participate:
Denmark, Germany, Greece, Spain, France, Italy, the Netherlands, Austria, Sweden and the UK.
149
The ADL-dependent population is estimated on the basis of data available from SHARE and
data on the numbers of people in institutions provided by Member States. The SHARE project
covers the population in households only, excluding the population in institutions. To estimate
the size of the elderly dependent population in the base year 2004,
• the elderly population in households is estimated, by subtracting the elderly population in
institutions as reported by Member States from the total elderly population, see next
section for details);
• number of dependent elderly people in households is estimated by applying the disability
rates in Table 5-5 to the estimated number of elderly people living in households;
• finally, the estimated number of dependent elderly persons living in households is added to
the number of elderly persons living in institutions to obtain the total dependent elderly
population.
The estimated number of dependent elderly people is presented on Table 5-6 for countries
where both SHARE data on disability rates are available as well as data from national sources
on the numbers of people living in institutions. In most countries, around 20% of the
population aged 65+ has some form of disability. For males this ranges from 12% in the
Netherlands to 27% in the UK, and for females from 19% in Denmark, the Netherlands and
Austria to 33% in the UK.
Table 5-6 Estimated elderly dependent population in 2004 for 8 EU Member States, in
thousands (based on SHARE data and reported number of people in
institutions)
65-69
DK
DE
ES
IT
NL
AT
SE
UK
Men
11
191
67
113
23
9
9
230
Women
16
183
83
124
24
19
13
285
70-74
Men
5
117
109
128
14
11
16
266
Women
10
340
150
310
34
22
15
329
75-79
Men
11
174
115
201
23
20
17
231
Women
11
414
189
337
44
27
36
356
80+
Men
27
390
189
299
51
12
62
361
Women
49
980
546
702
150
77
154
841
Total dependent population
aged 65+
Men
Women
54
86
873
1,917
480
968
741
1,473
111
251
52
145
104
218
1,088
1,811
as a % of total
population aged 65+
Men
Women
16
19
15
22
16
23
16
23
12
19
11
19
16
25
27
33
Source: SHARE, 1+ ADLs, AWG population scenario reported in EPC and European Commission (2005a)
Note: Estimates of the number of people in institutions by age are made for Denmark, Spain, the Netherlands
and Sweden.
Using the average disability rates, by age and gender in Table 5-5, a projection for the size of
the disabled population has been made for eleven additional EU countries in 2004. This
reported on Table 5-7. Approximately, 17% of males and 23% of females aged 65+ are
assumed to be disabled (with small differences due to diverge in the age structure of
populations in 2004).
150
Table 5-7 Estimated size of dependent population in 2004 using ‘average’ dependency
rates by age and gender from SHARE data, in thousands
Total dependent population
as a%of total
aged65+
populationaged65+
Men Women Men Women Men Women Men Women
Men
Women
Men
Women
20
28
26
43
33
55
53
159
132
284
18
27
5
7
6
9
8
11
13
32
32
59
16
23
1
1
1
1
1
2
2
5
4
9
16
24
9
13
10
19
15
25
22
70
55
128
17
26
18
29
20
41
25
46
31
90
93
206
17
24
6
11
7
15
7
17
9
31
29
75
16
22
4
8
4
10
4
11
4
20
16
49
13
19
1
1
1
1
1
2
2
4
5
8
21
28
61
91
68
124
71
136
84
251
284
601
15
20
10
12
10
17
11
19
14
35
44
83
19
21
3
5
4
8
4
9
5
19
16
41
14
22
65-69
BE
IE
LU
FI
CZ
LT
LV
MT
PL
SK
SI
Note:
70-74
75-79
80+
Estimates of the number of people in institutions by age are made for Ireland, the Czech Republic,
Poland and Slovakia.
Table 5-8 presents an overall estimated of the disabled population for EU10, EU15 and EU25
(countries for which it is available), made by combing the projections of the total disabled
population using SHARE data with the projections based on an average disability rate (on
Table 5-5).
Table 5-8 Total dependent population estimated, EU25, in thousands
65-69
EU15
EU10
EU25
Men
688
102
791
Women
795
157
952
70-74
Men
710
113
824
Women
1,284
215
1,498
75-79
Men
848
123
971
Women
1,505
240
1,745
80+
Men
1,480
148
1,628
Women
3,764
451
4,216
Total dependent population
aged 65+
Men
Women
3,727
7,348
487
1,063
4,214
8,411
as a % of total
population aged 65+
Men
Women
16
24
17
22
16
23
Source: SHARE, 1+ ADLs, EPC population projection
Note: The following Member States are included: Belgium, Denmark, Germany, Spain, Ireland, Luxembourg,
Italy, the Netherlands, Finland, Sweden, the UK, the Czech Republic, Lithuania, Latvia, Malta,
Poland, Slovakia and Slovenia.
151
Table 5-9 Estimated ADL-dependent population aged 65 and above, 2004
Dependent
population
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
Population receiving formal care in
institutions
000s
as % of
65+
000s
share of dependent
population
receiving care
416
23
147
35
Population receiving formal care
at home
000s
share of
dependent
population
receiving care
114
27
139
17
13
10
176
126
2790
19
535
19
975
35
1449
20
158
11
286
20
32
91
20
20
22
29
2214
20
193
9
933
42
13
20
3
23
4
33
362
16
79
22
197
16
183
22
57
31
52
28
322
21
102
32
142
44
2899
30
278
10
440
15
299
21
77
26
56
19
103
20
24
23
5
5
65
17
5
8
4
5
13
25
6
48
5
37
885
18
105
12
44
5
127
20
31
24
37
29
58
19
12
20
10
18
Source: National data, SHARE and ECFIN calculations
Table 5-9 presents the estimated number of dependent elderly people in 2004. In most
Member States, around 20% of the elderly population aged 65+ is dependent. About 20% of
the estimated dependent population receives long-term care in an institution and about 30%
receives formal care at home: hence some 50% of people considered dependent receive no
formal care financed by the State and instead rely on informal or no care. Differences across
Member States are wide and reflect the variety of institutional arrangements in the provision
of long-term care.
152
5.3.3.
Public spending on different types of formal care and unit costs
Eighteen countries provided data on public spending on long-term care. Of those, fifteen were
able to provide data on spending on care in institutions68, seventeen as regards spending on
care at home and thirteen as regards cash transfers. In general terms, spending is greatest on
care institutions. In EU15 countries, considerable resources are also spent on formal care at
home, which is negligible in the EU 10 countries.
By combining the data on public spending on different types of care with the data on numbers
of persons receiving care, it is possible to calculate the unit cost per beneficiary. For EU15
countries, the average cost per person receiving care in an institution is expensive at close to
€24000, and in seven Member States exceeds 70% of GDP per capita. The average cost of
providing formal care at home is €9373 per beneficiary. Cash transfers amount to €4619 per
person receiving aid.
Nominal spending per person on formal care is much lower in EU10 countries amounting to
an average of €3745 for care in institutions, €739 for care at home and €430 for countries
reporting cash benefits.
Table 5-10 Total public expenditure on long-term care, all ages, 2004, as a % of GDP
Institutional care
BE
DK
DE
ES
IE
IT
LU
NL
FI
SE
UK
CZ
LT
LV
MT
PL
SK
SI
EU15
EU10
Nominal euros
in billions
1.43
0.36
11.65
1.45
0.52
5.50
0.12
2.15
1.62
7.57
4.20
0.18
0.07
0.04
0.02
0.11
0.08
0.18
Unit cost
9067
23129
18517
8275
24477
19352
37199
23129
24343
62972
12824
1270
1878
3945
1732
1160
2970
13260
23935
3745
Home-based care
% GDP per
capita
33
64
70
42
68
83
66
81
85
203
45
15
36
83
16
23
48
102
Nominal euros
in billions
0.85
1.86
5.04
0.63
0.14
6.69
0.10
0.61
3.12
12.80
0.06
0.00
0.01
0.01
0.00
0.04
0.01
Unit cost
6520
7947
3886
2832
3887
3717
16410
10097
16579
21856
1792
312
731
588
91
1219
440
9373
739
Cash benefits
% GDP per
capita
24
22
15
14
11
16
29
Nominal euros
in billions
0.14
Unit cost
1106
% GDP per
capita
4
4.38
2.51
0.21
8.63
3740
5981
8857
6589
14
30
24
28
35
53
76
21
6
15
5
2
20
3
0.36
1439
5
0.03
0.01
274
71
3
1
0.01
0.10
0.11
0.06
113
823
869
1
16
14
4619
430
Source: National data and ECFIN calculations
5.4.
Projected size of the dependent population up to 2050 and projected number
of persons receiving different types of care
Table 5-11 presents the projected numbers of dependent people and of people receiving longterm care, both formal and informal, under the ‘pure ageing scenario’. The dependent
population is projected to increase by about 120%. Note, this is larger than the projected
increase in the old-age dependency ratio, and reflects the fact that it is the oldest-old (aged 80
and above) who will have the most dynamic population growth. While the probability of
receiving care is assumed to remain constant, the share of the population aged 65 and above
increases. The number of people receiving long term-care is projected rise in all Member
States. According to the projection, the population receiving formal care in institutions would
68
In addition, total expenditure in institutional care in the Netherlands was estimated using available
information on people in institutions and EU15 average unit cost.
153
rise by about 140% on average and as regards long-term care at home, by about 130%. The
population receiving informal or no care would increase by about 100% on average. On
average, about 45% of the dependent population is projected to rely on informal or no care,
ranging from less than 60% in Sweden and Latvia to over 120% in Spain, Ireland,
Luxemburg, the Netherlands, Poland, Slovakia and Slovenia.
Table 5-12 shows the projection of the dependent population under the ‘constant disability
scenario’. The dependent population is projected to increase by about 40%, a smaller increase
relative to the ‘pure ageing scenario’. Compared to 2004, higher increases are projected in the
population in institutions compared to the population receiving formal care at home in most
Member States. In 2050, the dependent population receiving formal care at home is projected
to be larger than the population receiving care in institutions, in most EU15 Member States
except in Belgium, Lithuania, Latvia, Malta, and Slovakia.
154
Table 5-11
Projection of dependent population, in thousands – pure ageing scenario
Dependent population
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
Population receiving formal care
in institutions
2004
2050
2004-50 % change
2004-50
147
331
184
125
13
29
16
117
535
1321
786
147
Population receiving formal care
at home
2004
2050 2004-50 % change
2004-50
114
247
133
116
176
368
192
109
975
2100
1125
115
Population receiving informal
or no care
2004
2050 2004-50 % change
2004-50
154
263
108
70
1280
2269
989
77
2004
2050
2004-50
416
139
2790
841
275
5689
425
136
2900
% change
2004-50
102
97
104
1449
3494
2045
141
158
348
190
120
286
667
380
133
1004
2480
1475
147
91
2214
13
362
197
319
4272
35
833
419
228
2058
22
471
221
250
93
173
130
112
20
193
3
79
75
403
10
194
55
211
7
116
274
109
221
147
29
933
4
109
1798
12
80
865
8
274
93
178
42
1088
6
135
2071
14
93
983
8
222
90
143
183
322
2899
374
569
5564
191
247
2665
104
77
92
57
102
278
130
188
619
73
86
341
128
85
123
52
142
440
113
254
934
61
112
494
117
79
112
74
79
2181
131
127
4011
57
48
1829
78
61
84
299
625
326
109
77
162
85
110
56
118
62
110
166
344
179
108
103
65
19
885
127
58
12631
11075
1556
184
99
49
2004
309
135
26089
22685
3404
80
34
31
1119
182
77
13459
11610
1848
78
52
166
126
143
134
107
105
119
24
5
13
105
31
12
1850
1585
265
44
8
34
251
78
30
4255
3649
606
20
3
21
146
47
18
2405
2064
341
87
59
172
140
153
155
130
130
129
5
4
5
44
37
10
3312
3151
161
10
6
13
105
94
24
6970
6601
369
5
2
8
61
57
13
3657
3449
208
87
59
170
140
153
131
110
109
129
74
57
1
737
59
36
7038
5909
1129
129
85
2
1648
137
82
13929
11500
2429
55
29
1
911
78
46
6891
5592
1300
74
51
95
124
133
128
98
95
115
Source: DG ECFIN calculation
Table 5-12
Projection of dependent population, in thousands – constant disability scenario
Dependent population
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
Population receiving formal care
in institutions
2050
2004- % change difference
2050
2004-50
in 2050
from pure
ageing
229
81
55
-103
20
6
48
-9
930
396
74
-390
Population receiving formal care
at home
2050 2004- % change difference
2050
2004-50
in 2050
from pure
ageing
166
52
45
-81
245
69
39
-123
1417
442
45
-683
Population receiving informal
or no care
2050 2004- % change difference
2050
2004-50
in 2050
from pure
ageing
152
-2
-1
-110
0
1383
104
8
-885
2050
20042050
% change
2004-50
547
179
3731
131
39
941
32
28
34
difference
in 2050
from pure
ageing
-294
-97
-1959
2224
775
53
-1270
200
42
26
-148
408
122
43
-258
1616
611
61
-864
199
2698
23
543
263
108
484
10
181
66
118
22
76
50
34
-120
-1574
-13
-290
-155
51
272
7
127
31
79
4
48
153
41
125
61
-24
-131
-3
-68
73
1151
8
44
218
4
153
23
81
-35
-647
-4
75
1275
8
33
187
3
78
17
45
-60
-796
-5
0
0
242
378
3408
59
56
509
32
17
18
-132
-191
-2156
89
134
428
33
32
151
57
31
54
-40
-55
-191
76
172
624
24
30
184
46
22
42
-37
-82
-310
77
73
2355
3
-6
174
4
-8
8
-55
-55
-1655
377
77
26
-248
99
22
28
-63
72
16
28
-46
205
40
24
-139
114
61
30
1226
185
85
16513
14434
2078
11
-4
11
341
58
27
3882
3359
523
11
-6
61
39
46
47
31
30
34
-69
-38
-20
-778
-124
-50
-9577
-8251
-1326
28
5
21
156
47
20
2861
2486
375
5
0
8
51
16
8
1011
901
110
19
0
66
49
53
70
55
57
41
-16
-3
-13
-95
-31
-10
-1394
-1163
-231
6
4
8
65
57
15
4567
4341
227
1
0
3
21
20
5
1255
1189
66
19
0
67
49
53
46
38
38
41
-4
-2
-5
-40
-37
-9
-2402
-2260
-142
80
52
1
1006
82
50
8491
1476
1476
6
-4
0
269
22
15
1453
-4432
347
8
-7
-19
36
38
41
21
-75
31
-50
-33
-1
-643
-56
-31
8229
1476
-792
Source: DG ECFIN calculation
156
5.5.
Projected spending on long-term care
5.5.1.
Pure ageing scenario
Table 5-13 presents the projection results for the ‘pure ageing scenario’ under the assumption
that costs evolve in line with GDP per worker (scenario I). Public spending on long-term care
is projected to increase by between 0.7 and 1.4 p.p. of GDP in most countries between 2004
and 2050. Given their well developed system of formal care provision, public spending is
projected to rise by over 2 p.p. in Finland, Sweden and Slovenia. Public spending is projected
to rise by less than 1 p.p. in EU10 Member States, except Slovakia and Malta. The striking
differences across countries (for example, a projected increase of only 0.1pp of GDP by 2050
in Poland) reflect differences in the level of spending in the base year.
Table 5-13 Projection results for the pure ageing scenario (I)
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
E U 25
E U 15
E U 10
2004
0 .9
1 .1
1 .0
P r o je c te d s p e n d in g a s % o f G D P
2010
2020
2030
2040
1 .0
1 .1
1 .4
1 .8
1 .2
1 .3
1 .9
2 .3
1 .0
1 .3
1 .5
1 .8
2050
2 .1
2 .6
2 .3
2 0 0 4 -2 0 5 0
1 .2
1 .4
1 .3
0 .5
0 .5
0 .5
0 .6
0 .7
0 .8
0 .3
0 .6
1 .5
0 .9
0 .5
0 .6
0 .6
1 .5
1 .0
0 .5
0 .7
0 .6
1 .6
1 .1
0 .6
0 .8
0 .8
1 .8
1 .2
0 .8
1 .0
1 .0
2 .0
1 .5
1 .0
1 .2
1 .3
2 .4
1 .7
1 .2
1 .5
0 .7
0 .8
0 .8
0 .7
0 .9
1 .7
3 .8
1 .0
1 .9
3 .7
1 .0
2 .3
3 .9
1 .1
3 .2
5 .3
1 .4
3 .8
5 .8
1 .7
4 .0
6 .3
2 .0
2 .2
2 .4
1 .0
0 .3
0 .3
0 .4
0 .6
0 .7
0 .8
0 .5
0 .5
0 .4
0 .9
0 .1
0 .7
0 .9
0 .9
0 .9
0 .2
0 .6
0 .4
0 .9
0 .1
0 .8
1 .1
0 .9
0 .9
0 .3
0 .6
0 .5
0 .9
0 .1
0 .8
1 .3
1 .0
1 .0
0 .3
0 .7
0 .6
1 .1
0 .1
0 .9
1 .6
1 .2
1 .2
0 .4
0 .8
0 .7
1 .2
0 .2
1 .2
2 .1
1 .4
1 .5
0 .4
1 .0
0 .8
1 .2
0 .2
1 .4
2 .4
1 .7
1 .7
0 .5
0 .5
0 .4
0 .4
0 .1
0 .7
1 .5
0 .8
0 .8
0 .3
Source: DG ECFIN calculation
Note:
EU25, EU15 and EU10 – average weighted by GDP
Taking account of existing policy settings in the Member States: the German long-term care system
In the EPC projection of public expenditure on long-term care, unit costs are indexed to GDP per worker or GDP
per capita. Under existing rules in Germany, all long-term care benefits (that is the benefits paid out by the
public insurance for people receiving formal care at home, care in institutions or cash benefits) are fixed by law
without any indexation. The difference between the amounts financed by the State and the costs of long term
care are either recovered by private insurance or are paid by the beneficiaries themselves.
To better reflect the current setting in German legislation, an alternative projection has been run where unit costs
of long-term care services are assumed to remain constant in real terms. This would mean that the amounts
financed by the State are adjusted in line with prices. The table below presents the results of the projection
assuming an indexation of unit costs to prices and to GDP per worker, respectively.
Assuming constant unit costs in real terms, the long-term care public expenditure is projected to remain around
1% of GDP over the whole projection period, as compared to an increase from close to 1% of GDP today up to
2% of GDP when assuming unit costs evolve in line with GDP per worker. The results of the two scenarios
illustrate the difference between what the State is projected to spend under these two assumptions (under current
legislation there would not even be an indexation to prices).
Projected spending on long-term care in Germany under existing legislation
2004
2010
2020
2030
2040
2050 change 2004-2050
AWGreference scenario
Unit costs are constant in real terms
0.97
0.96
0.99
0.94
0.97
1.00
1.02
1.21
1.36
1.64
2.00
Unit costs evolve inline withGDPper worker 0.97
Pure ageing scenario
Unit costs are constant in real terms
0.97
0.98
1.03
1.01
1.06
1.12
0.97
1.03
1.26
1.46
1.81
2.25
Unit costs evolve inline withGDPper worker
5.5.2.
0.03
1.03
0.15
1.28
Unit costs evolve in line with GDP per capita
Table 5-14 presents the projection results for the scenario under the assumption that ‘unit
costs evolve in line with GDP per capita’. It also compares the results relative to the ‘pure
ageing scenario’ presented on Table 5-13. The increase in spending projected is somewhat
smaller at the end of the projection period. Compared to the pure ageing scenario where unit
costs evolve in line with GDP per worker, the differences are very small. Spending would
tend to be higher in the first period of the projection and lower in the second period; this
reflects the different patterns in the evolution of GDP per capita and GDP per worker.
Table 5-14
Projection results for the scenario where unit costs evolve in line with GDP
per capita (II)
P r o je c te d s p e n d in g a s % o f G D P
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
E U 25
E U 15
E U 10
Source:
Note:
2004
0 .9
1 .1
1 .0
2010
1 .0
1 .2
1 .1
2020
1 .2
1 .3
1 .3
2030
1 .3
1 .8
1 .5
2040
1 .7
2 .0
1 .8
2050
2 .0
2 .4
2 .2
D iffe re n c e a s % o f G D P c o m p a re d to
p u r e d e m o g ra p h ic s c e n a r io
2010
2030
2050
0 .0
0 .0
-0 .1
0 .0
-0 .1
-0 .2
0 .0
0 .0
-0 .1
0 .5
0 .5
0 .6
0 .6
0 .7
0 .8
2 0 0 4 -2 0 5 0
1 .1
1 .2
1 .2
:
0 .2
0 .0
0 .0
-0 .1
0 .6
1 .5
0 .9
0 .5
0 .6
0 .6
1 .6
1 .0
0 .5
0 .7
0 .7
1 .7
1 .2
0 .6
0 .8
0 .8
1 .8
1 .3
0 .8
0 .9
1 .0
2 .0
1 .7
1 .0
1 .1
1 .3
2 .2
2 .1
1 .1
1 .4
0 .7
0 .7
1 .3
0 .7
0 .8
0 .0
0 .1
0 .1
0 .0
0 .0
0 .0
0 .1
0 .1
-0 .1
0 .0
-0 .1
-0 .1
0 .4
-0 .1
-0 .1
1 .7
3 .8
1 .0
1 .9
3 .8
1 .0
2 .2
3 .8
1 .1
3 .0
5 .1
1 .4
3 .6
5 .5
1 .6
3 .7
6 .0
1 .9
2 .0
2 .2
0 .9
0 .0
0 .1
0 .0
-0 .2
-0 .2
-0 .1
-0 .3
-0 .3
-0 .1
0 .3
0 .4
0 .4
0 .5
0 .6
0 .7
0 .4
0 .0
0 .0
-0 .1
0 .5
0 .4
0 .9
0 .1
0 .7
0 .9
0 .9
0 .9
0 .2
0 .6
0 .5
0 .9
0 .1
0 .8
1 .1
0 .9
0 .9
0 .3
0 .7
0 .6
1 .0
0 .1
0 .9
1 .3
1 .0
1 .0
0 .3
0 .7
0 .6
1 .1
0 .2
1 .0
1 .5
1 .2
1 .2
0 .4
0 .8
0 .7
1 .2
0 .2
1 .2
1 .9
1 .3
1 .4
0 .4
1 .0
0 .8
1 .2
0 .2
1 .3
2 .1
1 .6
1 .6
0 .5
0 .5
0 .4
0 .3
0 .1
0 .6
1 .1
0 .7
0 .8
0 .2
0 .0
0 .0
0 .0
0 .0
0 .0
0 .0
0 .0
0 .0
0 .0
0 .1
0 .0
0 .0
0 .0
0 .1
-0 .1
0 .0
0 .0
0 .0
0 .0
0 .0
0 .0
0 .0
-0 .1
-0 .4
-0 .1
-0 .1
-0 .1
DG ECFIN calculation
EU25, EU15 and EU10 – average weighted by GDP
158
5.5.3.
Constant disability scenario
Table 5-15 presents the projection results for the ‘constant disability scenario’, under the
assumption that costs evolve in line with GDP per worker. As expected, an improved
disability status would lead to a considerably lower number of disabled persons in the future
who would have some need for care. Under the constant disability scenario, the projected
increase in spending due to ageing would be between 40% and 60% lower (up to 100% in
Luxemburg) as compared to the pure ageing scenario. According to the projection, spending
would increase by about 0.5 p.p. of GDP in most countries, with smaller increases in EU10
Member States.
Table 5-15
Projection results for the constant disability scenario (III)
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
Difference as % of GDP compared to
pure demographic scenario
2010
2030
2050
0.0
-0.2
-0.5
-0.1
-0.3
-0.7
0.0
-0.2
-0.5
2004
0.9
1.1
1.0
2010
0.9
1.1
1.0
2020
1.0
1.2
1.1
2030
1.1
1.6
1.3
2040
1.4
1.8
1.5
2050
1.5
1.9
1.8
2004-2050
0.7
0.8
0.8
0.5
0.5
0.5
0.5
0.6
0.7
0.2
0.0
0.0
-0.1
0.6
1.5
0.9
0.5
0.6
0.6
1.5
0.9
0.5
0.7
0.6
1.5
1.0
0.5
0.8
0.7
1.6
1.0
0.7
1.0
0.8
1.8
1.1
0.8
1.2
1.0
2.0
1.3
0.9
1.5
0.4
0.5
0.4
0.4
0.9
0.0
0.0
0.0
0.0
0.0
-0.1
-0.1
-0.2
-0.2
0.0
-0.3
-0.3
-0.4
-0.3
0.0
1.7
3.8
1.0
1.8
3.6
1.0
2.0
3.5
1.0
2.7
4.5
1.2
3.0
4.6
1.3
3.0
4.7
1.5
1.3
0.9
0.5
-0.1
-0.2
0.0
-0.5
-0.9
-0.2
-0.9
-1.5
-0.5
0.3
0.3
0.3
0.5
0.5
0.6
0.3
0.0
-0.1
-0.2
0.5
0.4
0.9
0.1
0.7
0.9
0.9
0.9
0.2
0.5
0.4
0.9
0.1
0.8
1.1
0.8
0.9
0.3
0.5
0.5
0.9
0.1
0.7
1.2
0.9
0.9
0.3
0.6
0.5
1.0
0.1
0.8
1.4
1.0
1.1
0.3
0.7
0.6
1.1
0.2
1.0
1.7
1.1
1.2
0.4
0.8
0.6
1.0
0.2
1.2
1.9
1.3
1.4
0.4
0.3
0.2
0.1
0.1
0.5
1.0
0.5
0.5
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.1
-0.1
-0.1
0.0
-0.1
-0.2
-0.2
-0.2
0.0
-0.2
-0.2
-0.2
0.0
-0.2
-0.5
-0.4
-0.4
-0.1
Source: DG ECFIN calculation
Note:
EU25, EU15 and EU10 – average weighted by GDP
5.5.4.
Increase in formal care provision scenario
The entire age-related expenditure projection exercise is founded upon an assumption of “no
policy change”. However, as shown in the results for the pure ageing scenario, the projected
increase in public spending on long-term is much higher in countries with well developed
formal care systems and vice versa. Extrapolating forward on the basis of existing policies
and expenditure patterns may give a misleading picture of possible future pressures on public
finances. Countries with low levels of formal care provision today (and thus low levels of
public spending) will also witness a very large increase in the projected numbers of persons in
need of care, and thus pressure may emerge in the future for policy changes to increase formal
159
care provision. The gap between the need for care and supply of formal care will grow (i.e.
the difference projected number of persons with disability on Table 5-11 and the projected
numbers of person receiving formal care on the same table).
In brief, the headline projected change in public spending on long-term care may not fully
capture the scale or nature of the policy challenge. Growing numbers of elderly persons in
need of care may lobby governments to enact policy changes to increase the availability of
formal care. On top of the effects of growing numbers of elderly persons, the supply of
informal care within households may diminish, as family sizes decline and more women are
in active employment (although the scale of this effect will depend on the starting
employment rates of women).
To capture the budgetary effects of possible future policy changes, a scenario has been
devised which quantifies the budgetary impact of more formal care being provided/financed
by the public sector. In particular, it assumes that until 2020, the number of persons receiving
informal (or no) care falls by 1% per annum: half of these persons are assumed to receive
formal care in institutions and the other half would receive formal care at home.
Table 5-16 shows the projection of the dependent population under the ‘increase in formal
care provision scenario’. According to the projection, the population receiving formal care in
an institution would increase by 350% on average and the population receiving formal care at
home by 400%. The population relying on informal or no care would fall by about 90% on
average, 60% in the EU15 and 130% in the EU10. In 2050, the number of people receiving
informal or no care in 2050 would be about 20% of the dependent population on average.
Table 5-16
Projection of dependent population, in thousands – increase in formal
care provision
Dependent population
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
2050
20042050
% change
2004-50
Population receiving formal care
in institutions
2004- % change difference in
2050
2004-50
2050 from
pure ageing
405
258
175
73
841
275
5689
425
136
2900
102
97
104
1956
1421
266
635
Population receiving formal care
at home
2004- % change difference in
2050
2004-50
2050 from
pure ageing
321
207
181
73
334
158
90
-34
2735
1760
181
635
3494
2045
141
1042
884
559
694
1361
1074
375
319
4272
35
833
419
228
2058
22
471
221
250
93
173
130
112
113
983
14
373
93
790
11
294
462
411
347
374
38
580
4
179
146
2378
16
117
1444
12
374
569
5564
191
247
2665
104
77
92
167
224
1742
110
122
1464
193
120
527
37
36
1123
149
289
2057
625
326
109
259
181
235
96
184
99
37
2004
309
135
26077
22685
3391
80
34
24
1119
182
77
26019
22658
-489
78
52
181
126
143
134
6254
83066
-13
80
32
21
712
116
53
8290
7018
1272
57
27
14
608
85
41
6446
5433
1013
240
545
228
581
277
352
350
343
391
36
24
1
461
38
23
4050
3369
680
2050
2050
Population receiving informal
or no care
2004- % change difference in
2050
2004-50
2050 from
pure ageing
116
-39
-25
-147
2050
998
-281
-22
-1270
694
1091
87
9
-1388
405
155
266
38
580
4
60
912
6
17
-177
0
42
-16
7
-76
-1160
-8
97
148
1617
188
104
368
37
36
1123
58
56
1765
-16
-23
-416
-22
-29
-19
-74
-71
-2245
215
158
281
96
151
-14
-9
-193
46
30
14
566
132
47
10836
9786
1049
41
26
9
523
95
36
7523
6635
888
759
734
195
1195
256
355
6578
3777
91
36
24
1
461
38
23
3866
3185
680
57
38
2
725
60
36
6131
5062
1070
-17
-19
0
-11
1
0
-907
-847
-60
-23
-33
-4
-2
2
1
-13
-14
-5
-72
-48
-2
-923
-77
-46
-7800
-6439
-1361
Source: DG ECFIN calculation
Table 5-17 presents the projection results under the assumption of a policy change in the
provision of formal care, as well as the comparison with the results of the pure ageing
160
scenario. An increase in the provision of formal care, where the population who were
receiving informal care is split in half between home care and institutions, would result in
increases in public spending of more than 100% in many countries: Spain, Italy, Luxemburg,
the Netherlands, the UK, Lithuania, Latvia and Poland. Relative to the pure ageing scenario
where the probability of receiving formal care is kept constant during the projection period,
expenditure in 2050 would be higher by between 0.6 and 1 p.p. in most Member States.
Table 5-17 Projection results for the increase in formal care provision scenario (IV)
Projected spending as % of GDP
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
Difference as % of GDP compared to
pure demographic scenario
2010
2030
2050
0.1
0.2
0.3
2004
0.9
2010
1.0
2020
1.3
2030
1.5
2040
2.0
2050
2.3
2004-2050
1.5
1.0
1.1
1.6
1.8
2.3
2.8
1.8
0.1
0.3
0.6
0.5
0.7
0.9
1.0
1.3
1.7
1.1
0.6
1.5
0.9
0.5
0.6
1.7
1.1
0.7
0.7
2.1
1.4
1.1
1.0
2.3
1.5
1.5
1.2
2.8
1.8
1.9
1.6
3.3
2.1
2.3
1.0
1.7
1.2
1.8
0.1
0.0
0.0
0.2
0.1
0.2
0.4
0.0
0.2
0.6
0.3
0.7
0.9
0.0
0.3
0.9
0.4
1.0
1.7
3.8
1.0
2.0
3.9
1.4
2.6
4.2
2.0
3.7
5.8
2.5
4.4
6.2
3.0
4.6
6.8
3.6
2.8
3.0
2.6
0.1
0.1
0.3
0.5
0.4
1.1
0.6
0.5
1.6
0.3
0.4
0.6
0.8
1.0
1.2
0.9
0.1
0.3
0.4
0.5
0.4
0.9
0.1
0.7
0.9
0.9
0.9
0.2
0.7
0.9
0.9
0.2
0.8
1.3
1.0
1.0
0.3
0.9
1.8
0.9
0.2
0.9
1.9
1.3
1.4
0.4
1.0
2.0
1.1
0.3
1.1
2.3
1.6
1.7
0.6
1.2
2.5
1.3
0.4
1.5
3.1
1.9
2.0
0.7
1.5
3.0
1.3
0.4
1.8
3.6
2.3
2.4
0.9
1.0
2.6
0.4
0.3
1.1
2.7
1.5
1.5
0.6
0.1
0.5
0.0
0.0
0.1
0.2
0.1
0.1
0.1
0.3
1.4
0.0
0.1
0.2
0.7
0.4
0.4
0.2
0.6
2.2
0.0
0.2
0.4
1.2
0.7
0.7
0.3
Source: DG ECFIN calculation
Note:
EU25, EU15 and EU10 – average weighted by GDP
5.5.5.
AWG reference scenario
An ‘AWG reference scenario” (V) is a prudent scenario that aims to bring together several
different drivers of long-term care spending. It assumes that age-specific disability rates fall
by half of the projected decrease in age-specific mortality rates. This implies that some half of
projected gains in life expectancy up to 2050 would be spent in good health and free of
disability. Note that that the aim is to facilitate the comparison of budgetary projections across
expenditure items, and thus it should be symmetrical with the “AWG reference scenario” for
health care.
Table 5-18 presents the results of the AWG reference scenario. It shows that the projected
increase in public spending lies midway between the results of the “pure ageing” and the
“constant disability” scenario. The effects of the “AWG reference scenario” are stronger for
long-term care than for health care, i.e. in terms of mitigating the projected increase in public
161
spending. This occurs because unlike the health care projection exercise, there is no
assumption regarding the income elasticity of demand being greater than unity. Also, the agespecific disability rates used in the long-term care projection rise at a much steeper pace
compared with the (implicit) assumptions on age-specific morbidity rates used in the health
care projection (which uses the age-related expenditure profile as a proxy for morbidity).
Table 5-18 Projection results for the AWG reference scenario
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
EU25
EU15
EU10
2004
0.9
1.1
1.0
Projected spending as % of GDP
2010
2020
2030
2040
0.9
1.1
1.3
1.6
1.1
1.2
1.8
2.0
1.0
1.2
1.4
1.6
2050
1.8
2.2
2.0
2004-2050
1.0
1.1
1.0
0.5
0.5
0.5
0.5
0.6
0.8
0.6
1.5
0.9
0.5
0.6
0.6
1.5
1.0
0.5
0.7
0.6
1.6
1.0
0.5
0.8
0.7
1.7
1.1
0.8
1.0
0.9
1.9
1.3
0.9
1.2
1.2
2.2
1.5
1.1
1.5
0.2
0.0
0.6
0.7
0.6
0.6
0.9
1.7
3.8
1.0
1.9
3.7
1.0
2.1
3.7
1.1
3.0
4.9
1.3
3.4
5.2
1.5
3.5
5.5
1.8
1.8
1.7
0.8
0.3
0.3
0.4
0.5
0.6
0.7
0.4
0.5
0.4
0.9
0.1
0.7
0.9
0.9
0.9
0.2
0.6
0.4
0.9
0.1
0.8
1.1
0.9
0.9
0.3
0.6
0.5
0.9
0.1
0.7
1.3
0.9
1.0
0.3
0.6
0.5
1.0
0.1
0.9
1.5
1.1
1.1
0.3
0.7
0.6
1.1
0.2
1.1
1.9
1.3
1.3
0.4
0.9
0.7
1.1
0.2
1.3
2.2
1.5
1.5
0.5
0.4
0.3
0.2
0.1
0.6
1.2
0.6
0.7
0.2
Source: DG ECFIN calculation
Note:
EU25, EU15 and EU10 – average weighted by GDP
5.6.
Conclusion
An ageing population will be a strong upward impact on public spending for long term care.
This is because frailty and disability rises sharply at older ages, especially amongst the very
old (aged 80+) which will be the fastest growing segment of the population in the decades to
come. The projection methodology has been upgraded considerably since the 2001 exercise,
and has enabled to run scenarios which examine non-demographic drivers of spending.
162
According to a “pure ageing” scenario based on current policy settings, public spending on
long-term care is projected to increase by between 0.5 and 1 p.p. of GDP between 2004 and
2050. The projected changes in public spending are very diverse reflecting very different
approaches to the provision/financing of formal care. Countries with very low projected
increases in public spending currently have very low levels of formal care. The projections
show that with an ageing population, a growing gap may occur between the number of elderly
citizens with disability who are in need of care (which will more than double by 2050) and the
actual supply of formal care services. On top of an ageing population, this gap could further
grow due to less informal care being available within households on account of trends in
family size and projected increase in the participation of women in the labour market. In brief,
for countries with less developed formal care systems today, the headline projected increase
in public spending on long-term care may not fully capture the pressure on public finances, as
future policy changes in favour of more formal care provision may be needed.
Public spending is very sensitive to trends in the disability rates of elderly citizens. Compared
with a “pure ageing” scenario, projected change in spending would be between 40% and 60%
lower if the disability status of elderly citizens improves broadly in line with the projected
increase in life expectancy. Policy measures, which can either reduce disability, limit the need
for formal care amongst elderly citizens with disabilities, or which favour formal care at home
rather than in institutions, can have a very large impact on public spending.
163
6.
EDUCATION
6.1.
Introduction
The number of children and young people in the EU is expected to fall over the next decades.
This has raised the question of whether savings in education expenditure can be expected. The
results presented in this chapter indicate a reduced ratio of students to working-age population
which leads to a reduction in the ratio of total education expenditure to GDP in all EU
Member States. While this ratio ranged from 3.4 to 7.6 % in 2002 (the base year), it is
projected to range from 2.4 to 7.5 % in 2050. The reductions are 1 percentage point or lower
in 18 Member States, and 2 percentage point or higher only in two countries. As the
reductions in education expenditure are relatively minor, they can not be expected to offset
the rise in old-age-related expenditure.
The exercise takes into account expected demographic and labour market developments and
the commonly agreed macroeconomic assumptions applied to the whole budgetary exercise. It
does not assume a general rise in the education levels, but analyses the effects of expected
demographic and labour market developments given the present enrolment and cost situation.
As a consequence, a word of caution is in order. The projections of reduced education
expenditure depend on a number of variables. As no underlying trend in enrolment rates is
included, wealth effects on the demand side, or investment considerations e.g. related to the
Lisbon objectives, could lead to savings being even more limited. The same can happen if
expenditure per student should rise relative to GDP per worker, e.g. because of smaller
classes or an increase in relative wages. In several Member States national expectations are
that enrolment and/or cost levels will increase more than what follows from the projections,
because of implemented or planned legislation or other policies. This is especially relevant for
enrolment in tertiary education. As education is to a large extent an investment in future
human capital, many Member States may also wish to direct any savings arising from
demographic developments to exactly such increases in quality or intensity.
Historical experience further emphasizes that factors other than demographic developments
have clearly been important to the developments of education expenditure over the last years.
The projected savings are conditional on these factors not continuing to point in an upward
direction. While a detailed analysis of such factors has been beyond the scope of the current
exercise, it is important to note that the projections should in no way be taken to imply that
large and easy savings can be expected for public finances due to developments in the
educational sector.
Compared to the exercise in 2003, several improvements have been implemented in the
current exercise. The main improvement lies in the more reliable and comparable data that
have been used in this exercise. The present calculation of enrolment rates further ensures
consistency between enrolment rates and labour market participation rates. The methodology
also allows different assumptions on the developments of each cost element. For details on
the methodology, refer to the Economic Policy Committee and European Commission
(2005a).
6.2.
Data collection and delimitation of the exercise
The data used have been collected from Eurostat, and then sent to the Member States for
information and verification. For some countries complete data were not available. In these
cases, simplifying assumptions have been made in order to run the projections; cf. Table 6-1.
Table 6-1: Detailed assumptions made in performing the projections
Country
Data situation
Belgium
Complementary information has been provided by
the Belgian authorities for year 2003 (number of
personnel). Financial information for level 2 and
level 3 are combined.
Assumptions made
Number of personnel has been
estimated for each level of education
applying to year 2002 the same ratio
student/personnel as in 2003.
Expenditure has been split between
level 2 and level 3/4 assuming that the
salary level is the same across the three
levels. For all other expenditure items
the ratio between different categories of
expenditure provided by the combined
figures is kept constant.
Denmark
Data for personnel are missing for level 2 and 5
Germany
The spending (around 0.25 per cent of GDP) at the
workplace for combined workplace and school
education as well as similar expenditure by
"Bundesagentur für Arbeit" is not included. These
data were provided by German authorities.
Estonia
Personnel data for 2002 are missing. Data for
Finance 2 (expenditure breakdown by type of
expenditure: personnel, other than personnel) are
missing
Data covers exclusively public spending
Number of staff in level 2 and 5 has
been estimated using EU15 average
class size.
The 2001 student/personnel ratio is
applied to the 2002 figures.
Assumption: Total public spending, as
from Finance1, has been broken down
in wage and no-wage related
expenditure according to EU25 ratio.
Greece
Financial data for level 2 and 3 are combined.
The salary level is assumed to be equal
across level 2 and 3. Other expenditures
are assumed to have the same ratio
between level 2 and 3 as salaries.
Spain
Financial data for levels 2 and 3/4 are combined.
The salary level is assumed to be equal
across level 2 and 3/4. Other
expenditures are assumed to have the
same ratio between level 2 and 3/4 as
salaries.
Ireland
Data for personnel for level 2 and 3/4 are
combined.
The data have been broken down
according to class size information
provided by Irish authorities.
165
Lithuania
Data for private payments are missing.
Financial data for level 1, 2 and 3/4 are combined.
Data for private payments (P5) have
been provided by the Lithuanian
authorities.
Financial data for levels 1, 2 and 3/4
have been broken down according to
number of teachers on the assumption
that the salary is equal across levels.
Luxembourg
Data cover only spending up to ISCED level 3.
Moreover figures represent exclusively public
spending in public institutions. These data were
provided by Luxembourg authorities.
Netherlands
Number of personnel in ISCED level 2 is missing.
Number of staff in level 2 has been
estimated using EU15 average class
size.
Portugal
Data for staff are missing for level 5
Number of staff in level 5 has been
estimated using EU15 average class
size.
Slovenia
Data for Fin1 in level 1 include data for level 2.
The salary level is assumed to be equal
across level 1 and 2.
No data for Fin2 (break down of expenditure by
type) exists.
United
Kingdom
Data for level 3 include data for level 2.
Assumption: Total public spending as
from Finance1, has been broken down
by wage and no-wage related
expenditure according to EU25 ratio
The salary level is assumed to be equal
across level 2 and 3. Other expenditures
are assumed to have the same ratio
between level 2 and 3 as salaries.
Source: Commission services
Education is classified into seven different levels according to a standard international
classification system (ISCED).69 The projections cover public education expenditure for
basic, upper-secondary and tertiary education. In particular:
69
Pre-primary education. Level 0 of ISCED classifications. It is defined as the initial stage of organised
instruction, designed primarily to introduce very young children to a school-type environment. Such
programmes are designed in general for children of at least 3 years. Basic (primary plus lower secondary)
education. Level 1 and 2 of ISCED classification. Level 1 is the start of compulsory education (the first stage
of basic education) with a legal age of entry usually not lower than five years old and higher than seven years
old. This level covers in principle six years of full-time schooling. Level 2 is lower secondary school ( or a
second stage of basic education). The end of this stage is usually after nine years of schooling after the
beginning of primary education and often coincides with the end of the compulsory education. It includes
general education as well as pre-vocational or pre-technical education and vocational and technical education.
Upper-secondary education. Level 3 and 4 of ISCED classification. Level 3 is upper-secondary school and the
entry is typically 15 or 16 year old. It also includes vocational and technical educational. Level 4 is postsecondary non-tertiary education and these programmes are typically designed to prepare students to the
following level (university). Tertiary education. Level 5 and 6 of ISCED classification. Level 5 covers at least
two years of education and the minimal access requirements is the completion of level 3 and 4. However a
Master course that implies up to 6 years of tertiary education is included in level 5. Level 6 includes tertiary
programmes which lead to the award of an advance research qualification. See Unesco, 1997.
166
a) Projections are run for primary (ISCED 1), lower secondary (ISCED 2), upper
secondary and post secondary non-tertiary (ISCED 3 and 4), and tertiary education
(ISCED 5 and 6). This allows distinguishing between compulsory schooling (ISCED 1
and 2), non compulsory schooling (ISCED 3 and 4) and tertiary education (ISCED 5
and 6). ISCED levels 4 and 6 play a marginal role. They are often assimilated to levels
3 and 5 respectively, and are treated as part of these levels also in this exercise.
b) The effective starting and ending age of each education level differ significantly
across Member States. In addition the effective upper age-limit can differ considerably
form the standard one70. However, data has been provided on all students across both
age and level. All students are thus included in the projections, and the differences
between standard ages and effective limits do not cause problems for the projections.
c) As this exercise focuses on comparability of data across countries, pre-primary
education is not included in the projections. The 2003 exercise revealed serious data
problems related to pre-primary education which makes it difficult to produce reliable
projections. Comparability across countries is also hampered by large differences in
the institutional settings of pre-primary systems and large shares of private
institutions. Public expenditures on pre-primary education on average represent less
than 0.5% of GDP.
The base year for the calculations is 2002. This is because 2002 is the last year for which a
complete data set, comprising both the number of students and staff and financial data, is
available. However, actual enrolment figures are also available for 2003 for all countries, and
these are therefore included. This implies that for 2003 projected enrolment corresponds to
actual enrolment, while cost levels are projected data which may differ somewhat from actual
developments.
6.3.
The number of students in public education
6.3.1.
Demographic developments
The main driving force for the future trend in the number of students is demographic
developments. While the AWG population scenario71 indicates a relatively stable total
population in the EU, much larger changes are expected in the composition of the population.
The starting and ending ages in education varies greatly between countries, and especially in
higher education, it is difficult to set an upper limit to the age where people are potentially
affected by education policies. However, a broad indication can be given by looking at the
number of people aged 5-25 years, as this is the most relevant age-group in most countries.
For the EU, this number is projected to decline from 117 million in 2002 to 91 million by
2050 (see Graph 6-1). The number of old people (aged 65 and above) will rise markedly over
the same horizon, and the number of old people will as a consequence be higher than that of
younger ones in less than 20 years.
70
A notable; but not the only; example here is Denmark, where according to national estimates approximately
2/3 of tertiary education students are over the standard age of 19-23.
71
See Section 2.1.
167
Graph 6-1: Population aged 5-25 and over 65 in the EU25 (2002-2050). Millions
(millions)
140
cohort 65+
130
120
110
100
cohort 5-25
90
80
70
60
2002
2007
2012
2017
2022
2027
2032
2037
2042
2047
Source: Eurostat.
The number of young people must be seen in relative terms to be a useful indicator of
expected changes in education expenditure as a share of GDP. Table 6-2 presents the size of
the populations aged 5-25 and their share of the working-age population in all Member States.
With the exception of The Netherlands, Luxembourg and Sweden, the size of the age group 525 is foreseen to contract between 2002 and 2050. The decline in the number of young people
is expected to exceed 40% in six countries (CZ, EE, LT, LV, PL, SK) and to be between 30%
and 40% in three countries (EL, HU, SI).
If the number of young people is instead considered in relation to the working-age population,
the table shows that the share of young people will fall in all countries except Denmark,
Luxembourg and the Netherlands. There were on average around 38 young out of 100 of
working-age in the EU in 2002, while in 2050 there will be about 35 out of 100. This overall
trend hides differences across countries. The biggest drops in young shares in absolute terms
are expected in Cyprus, Lithuania, Poland and Slovakia where the ratio will fall more than 10
percentage points. This decline is, however, very small relative to the expected rise in the oldage dependency ratio72, from 24 out of 100 in 2002 to 52 out of 100 in 2050.
72
The old-age dependency ratio is defined as the ratio between people aged 65 or older and the population aged
15-64.
168
Table 6-2: Change in population aged 5-25 and young share of working-age population
between 2002 and 2050.
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
EU
Total population (age 5-25) - in thousands
Change
2002
2050
2002- 2050
2603
2353
-250
2841
1641
-1200
1338
1279
-59
14458
-4591
19049
393
233
-161
2807
1942
-865
10356
7369
-2987
15845
14969
-875
1254
1210
-43
12618
9381
-3237
227
195
-32
674
382
-291
1043
574
-469
112
153
41
2792
1818
-974
119
110
-9
4094
4109
14
2006
1552
-454
12197
6452
-5745
2694
1928
-766
531
355
-176
1739
895
-844
1367
1150
-216
2307
2366
60
15648
13759
-1890
90634
-26019
116653
Young share1
2002
38.5
39.6
37.5
2050
37.4
32.7
39.1
change
2002-2050
-1.1
-7.0
1.6
34.2
42.9
37.6
36.9
41.0
47.5
33.0
48.2
42.3
45.1
37.6
40.1
44.1
37.5
36.7
46.2
38.6
38.0
46.3
39.3
40.1
40.4
32.1
34.7
33.0
32.1
40.0
38.2
32.0
33.0
34.5
33.4
38.9
35.1
35.5
38.9
33.0
33.3
35.0
33.4
32.7
38.2
39.1
36.4
-2.0
-8.2
-4.6
-4.8
-1.1
-9.3
-1.0
-15.2
-7.8
-11.6
1.2
-5.0
-8.6
1.3
-3.6
-13.0
-3.6
-4.6
-13.6
-1.2
-0.9
-3.9
38.4
34.8
-3.6
1
Young share is reported as ratio between population age 5-25 over population aged 15-64.
Source: Commission services calculations based on Eurostat data.
6.3.2.
Enrolment
Given the size of the population in relevant age groups, enrolment rates for each age group
decide the number of students73. For basic education (primary and low secondary) enrolment
rates tend to be close to 100%, and can be expected to remain broadly constant over time as
basic education is compulsory in all Member States. Frictions in the systems and lack of
enforcement of the legislation, nevertheless lead to some deviations from 100% enrolment.
73
The enrolment rate of people aged x is defined as the number of students aged x divided by the number of
people aged x in the total population. This is sometimes referred to as a net rate, while the gross rate is the
total number of students divided by the number of people in the age-group considered relevant. In 2003
gross rates had to be used as the age of the students was not available, but as the effective limits can exceed
the official age, this lead to gross rates above 100% in some cases. The available figures sometimes show
also net enrolment rates above 100%. This must be due to imprecise registration of either the age of the
students or the size of the population in question.
169
In the age-groups most frequently enrolled in upper secondary and tertiary education, working
constitutes an alternative. The combination of part-time studying and part-time working, is
also quite frequent in some countries, especially for tertiary education. Without any specific
reason to assume a shift in the number of part-time students, or in the number of young people
neither working nor studying, enrolment rates are calculated as a complement to labour
market participation rates74. This implies that, other things being equal, an increase in the
participation rate gives a decrease of the enrolment rate.75 Table 6-3 presents the projections
of participation rates for the age-groups most relevant to secondary and tertiary education.
Table 6-3: Labour market participation rates for young people (2002-2050)
Age 15-18
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
2002
6.6
4.3
54.3
23.0
4.5
9.2
15.1
9.6
23.1
13.3
5.0
9.5
4.0
9.1
2.9
32.8
61.3
35.7
6.5
20.0
7.7
5.8
27.8
24.7
44.7
2050
6.7
6.1
51.1
24.1
7.0
8.7
14.5
11.0
22.4
12.3
9.0
8.4
4.3
6.2
4.9
30.2
59.6
36.4
6.7
17.6
5.9
8.9
26.1
23.3
46.1
Age 19-24
Change 2002
- 2050
0.0
1.8
-3.3
1.1
2.5
-0.5
-0.6
1.3
-0.7
-1.0
4.0
-1.1
0.3
-2.9
2.0
-2.6
-1.6
0.7
0.2
-2.4
-1.8
3.2
-1.7
-1.3
1.4
2002
54.2
59.2
77.0
68.4
56.7
52.2
59.0
55.3
70.8
54.6
65.1
62.3
52.3
51.3
50.2
78.4
81.9
68.3
58.1
63.3
51.7
67.1
67.9
66.1
77.7
2050
55.8
56.1
79.0
68.9
59.6
51.0
60.3
58.5
73.2
52.9
69.2
64.2
50.0
43.5
48.6
77.2
82.7
69.9
59.2
61.5
47.3
63.0
69.5
69.7
77.2
Change 2002
- 2050
1.6
-3.1
2.1
0.4
2.9
-1.2
1.3
3.3
2.4
-1.6
4.1
1.9
-2.3
-7.8
-1.6
-1.2
0.7
1.6
1.1
-1.7
-4.4
-4.1
1.7
3.6
-0.6
Source: Commission services calculations based on Eurostat data.
Labour market participation varies strongly across countries in the lower age group: while it is
below 10 per cent in half of the countries, it exceeds 50 per cent in Denmark and the
Netherlands. As enrolment rates for the same age-group are high also in these countries, this
entails that combining studies and work is common. In general, large shifts in labour market
participation rates for young people are not expected over the next decades.
As the age limits for the upper secondary and tertiary education levels vary, Table 6-4 and
Table 6-5 provide the combined enrolment rates for all levels of education by single year age
groups for 2002 and 2003 respectively. Not surprisingly, enrolment falls with age, and there
are wide variations between countries.
74
The participation rate is defined as the ratio of the labour force in a given age group to the total population in
that age group. Participation rates and total population in a determined age group are the ones used in other
parts of the budgetary projection exercise.
75
See EPC and COM (2005a) for details on the methodology.
170
A comparison between the two tables shows some difference in enrolment rates between 2002
and 2003. In most cases, enrolment is higher in 2003, hinting at an underlying upward trend.
This is why the projections include actual 2003 enrolment rates.
Table 6-4: Enrolment rate across all level of education by age1. 2002
Country/Age
15
16
17
18
19
20
21
22
23
24
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
100.9
100.0
95.7
98.5
98.9
92.7
99.3
97.4
106.0
95.3
94.3
97.9
100.4
91.6
97.4
103.8
102.6
94.4
96.8
93.5
102.6
98.8
99.2
99.2
109.6
99.7
100.0
91.2
99.4
98.3
92.7
92.5
96.7
95.1
88.2
88.6
95.8
97.9
84.9
89.7
60.2
100.7
91.4
93.7
83.0
94.8
94.5
96.1
97.0
87.0
103.1
98.3
83.0
94.2
91.1
69.7
80.6
91.0
83.6
80.9
78.4
91.6
95.0
80.1
86.0
59.6
88.4
88.3
90.7
71.2
94.3
87.5
93.9
96.0
74.7
91.8
87.5
78.3
85.7
77.0
75.9
67.2
79.6
82.6
74.8
23.2
76.6
85.2
70.3
73.3
56.6
76.8
69.3
85.0
60.5
83.8
63.8
89.3
93.6
57.1
79.3
63.1
60.0
67.4
65.7
89.5
57.1
65.5
59.1
52.4
28.3
61.7
70.0
50.1
59.7
36.7
63.1
43.9
72.6
52.0
71.0
37.2
48.5
43.3
55.8
65.8
40.3
45.1
50.6
56.6
56.3
51.5
51.1
51.2
41.4
22.5
48.7
57.1
30.4
46.8
27.1
56.0
31.4
66.2
45.9
45.5
27.0
47.3
45.3
52.1
53.3
30.3
44.3
40.9
46.0
45.0
44.3
40.1
41.7
35.8
21.0
41.6
45.7
16.6
37.6
20.0
48.9
27.5
55.4
41.9
44.6
24.4
55.8
47.6
42.0
41.0
26.3
43.3
51.1
34.7
35.9
36.8
32.2
27.0
31.0
13.3
41.6
35.9
8.6
31.1
11.6
37.7
24.7
47.4
36.4
39.9
22.5
57.3
46.1
31.5
30.0
22.1
41.6
26.1
26.6
25.4
30.6
24.5
16.4
27.0
9.5
26.3
28.7
4.3
24.2
5.9
29.4
22.3
41.1
29.4
34.8
16.0
51.9
43.0
26.3
22.7
16.3
38.1
21.3
22.6
21.4
23.4
16.9
11.6
24.0
7.0
20.8
21.6
2.5
19.2
4.3
22.6
19.7
27.7
21.6
24.5
10.1
44.5
38.1
23.7
1
Students studying abroad are taken into account in the country in which they study. This especially affects the figures for Luxembourg.
Source: Commission services calculation based on New Chronos database.
171
Table 6-5: Enrolment rate across all level of education by age1. 2003
Country/Age
15
16
17
18
19
20
21
22
23
24
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
102.3
100.0
100.7
97.5
98.1
91.8
98.5
97.4
105.3
96.9
96.0
96.3
100.7
90.0
99.8
102.2
101.6
94.3
97.6
88.8
99.0
99.7
99.2
99.3
105.9
101.1
100.0
92.8
96.5
98.5
94.0
92.1
96.3
97.5
88.4
93.1
95.9
100.1
86.2
92.9
85.4
94.8
90.8
95.8
84.6
98.5
94.4
96.3
97.0
87.6
104.4
98.6
86.0
93.1
91.5
65.4
81.9
91.9
84.6
82.1
80.9
92.1
95.1
79.6
85.5
63.2
85.4
88.3
92.3
73.1
95.5
90.1
94.1
97.4
75.2
88.5
88.3
80.9
86.8
79.3
68.3
68.8
79.5
85.5
77.6
28.4
78.9
87.4
71.4
75.9
42.8
76.2
69.7
85.4
61.2
85.7
72.2
92.0
94.5
53.8
76.5
64.3
60.9
69.1
64.2
90.3
56.9
66.2
60.4
55.4
17.6
63.4
72.0
49.1
63.5
36.2
65.5
44.4
75.5
51.2
75.4
44.3
51.7
42.5
52.2
67.6
44.9
43.0
51.4
53.9
55.1
50.9
51.9
54.7
44.0
37.6
50.2
58.0
30.0
50.0
27.7
57.3
31.9
67.7
44.3
47.4
28.4
49.7
45.2
50.2
53.1
32.1
45.5
42.4
45.0
44.1
42.1
40.7
43.1
39.6
25.0
42.7
48.9
17.5
41.0
23.7
50.7
28.8
57.8
40.2
45.6
24.7
57.0
47.3
39.9
41.5
25.0
43.3
51.7
34.9
34.9
35.7
32.4
28.7
32.4
18.3
43.5
40.9
8.8
33.4
15.9
39.6
26.0
49.9
34.8
41.2
23.1
57.9
47.2
30.0
30.4
20.4
42.6
27.5
25.7
25.2
28.5
24.3
16.8
27.8
16.2
27.5
33.2
4.9
25.9
9.1
30.1
23.0
43.8
28.1
35.6
17.4
54.4
44.2
24.8
23.7
16.5
38.6
22.4
21.3
21.1
22.1
17.3
12.0
22.4
10.9
21.1
24.3
2.8
20.1
6.4
24.0
20.4
28.5
21.8
27.2
11.8
46.2
39.5
22.5
1
Students studying abroad are taken into account in the country in which they study. This especially affects the figures for Luxembourg.
Source: Commission services calculation based on New Chronos database.
Table 6-6 shows that enrolment in 2050 is mostly rather close to enrolment in 2002 and 2003.
The changes from 2003 that do occur follow from developments in the labour market.
172
Table 6-6: Enrolment rate across all level of education by age1. 2050
Country/Age
15
16
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
102.5
100.0
100.7
97.5
98.1
91.9
98.5
97.3
105.3
96.9
96.0
96.3
100.7
91.0
99.8
102.2
101.6
94.2
97.6
88.8
98.9
99.7
99.2
99.4
105.9
101.5
99.9
92.8
95.2
98.5
94.0
92.6
95.7
96.2
88.4
93.1
94.8
100.1
84.0
92.8
85.3
94.8
87.9
95.0
83.6
98.5
94.1
93.4
97.0
85.9
17
104.0
96.2
81.2
91.7
91.5
64.2
82.2
91.2
84.4
81.1
80.9
92.1
95.0
80.0
83.7
62.5
85.4
87.6
92.3
71.5
94.7
87.7
94.1
97.4
72.2
18
19
20
21
22
23
24
88.7
83.1
80.6
83.0
77.9
72.2
67.0
79.4
84.5
77.8
27.4
78.9
84.6
70.0
70.7
41.0
74.5
69.6
85.4
60.5
85.1
61.7
92.0
94.3
51.3
75.3
57.9
59.9
67.1
62.2
86.5
57.3
66.2
60.0
54.7
14.5
61.1
72.0
45.8
58.4
31.3
62.5
42.7
72.1
50.6
72.9
40.0
51.6
41.7
50.9
65.9
41.3
42.1
49.9
50.6
55.7
50.2
51.8
49.3
42.3
35.1
46.9
55.5
25.3
47.2
26.4
53.5
30.8
63.4
42.8
47.3
28.4
48.7
42.2
48.6
51.5
31.1
34.4
42.0
43.6
47.3
40.8
39.9
38.7
39.0
20.1
44.8
47.4
16.3
39.7
21.8
47.4
28.3
54.1
39.0
47.8
26.1
49.5
42.7
37.7
39.7
28.3
34.7
53.2
39.7
35.9
34.7
31.2
25.5
32.1
18.7
38.1
44.8
7.5
33.0
15.9
37.1
25.7
45.9
33.9
45.6
25.2
55.2
38.9
29.7
30.1
23.8
30.4
28.7
27.1
27.2
26.3
22.4
15.1
28.4
17.4
29.4
41.9
4.5
26.7
7.6
30.0
20.0
41.0
26.2
41.5
19.5
50.8
35.2
24.8
23.7
19.1
31.1
19.4
23.1
24.3
21.9
14.6
10.5
22.9
9.0
20.9
32.0
2.8
23.5
4.2
21.8
20.9
27.4
21.7
34.1
13.6
42.3
32.3
20.2
1
Students studying abroad are taken into account in the country in which they study. This especially affects the figures for Luxembourg.
Source: Commission services calculation based on New Chronos database.
Given the projected trends of the above described variables, the number of students enrolled
in education in EU is expected to decline from 91.8 and 91.6 millions in 2002 and 2003
respectively to 71.7 millions in 2050. For all age groups the main explanation for the drop in
the number of students is demographics, but for students aged 15 or more, labour market
developments also influence the developments in enrolment rates. The number of students is
expected to decline from 2002 to 2050 in all countries but Luxembourg (see Table 6-7).
Measured as a share of working-age population, the average EU student ratio is expected to
decline by 2.4 percentage points. Declines in this ratio are expected in all countries but
Denmark and the Netherlands, and the strongest expected reductions are foreseen for Cyprus
and Poland with reductions of about 10 percentage points.
173
Table 6-7: Total number of students and student share of working-age population
Total number of students (in thousands)
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
EU25
Student share of working-age population1
(as a percentage)
2002
2050
change 20022050
2002
2050
change 20022050 (p.p)
2332.6
1935.3
1046.0
14442.9
304.0
1975.3
7461.2
11712.4
992.2
9198.7
141.5
510.1
796.6
69.0
1945.5
77.1
3208.1
1422.1
9098.3
1963.6
392.0
1108.5
1178.8
2114.8
16406.7
91833.3
2086.9
1164.3
964.6
10592.5
174.8
1443.8
5569.5
11003.7
992.1
7004.5
116.8
279.5
440.0
90.6
1324.3
71.3
3125.8
1056.7
4748.9
1461.5
281.7
589.5
967.2
2004.5
14154.5
71709.6
-245.7
-770.9
-81.5
-3850.3
-129.2
-531.5
-1891.7
-708.8
-0.1
-2194.2
-24.7
-230.6
-356.7
21.6
-621.1
-5.9
-82.2
-365.4
-4349.4
-502.1
-110.4
-519.0
-211.6
-110.3
-2252.1
-20123.8
34.5
27.0
29.3
25.9
33.2
26.5
26.6
30.3
37.6
24.1
30.0
32.1
34.4
23.1
27.9
28.7
29.4
26.0
34.5
28.1
28.0
29.5
33.9
36.7
42.3
30.2
33.2
23.2
29.5
24.3
26.1
24.6
24.3
29.4
31.3
23.9
19.8
25.2
25.6
23.0
25.6
23.1
29.6
22.5
24.5
26.5
26.5
21.5
32.1
33.2
37.5
27.8
-1.3
-3.8
0.2
-1.6
-7.1
-1.9
-2.3
-1.0
-6.3
-0.2
-10.2
-6.8
-8.8
-0.1
-2.4
-5.6
0.1
-3.5
-10.0
-1.6
-1.6
-8.0
-1.8
-3.6
-4.9
-2.4
1
Working-age population is defined as population aged 15-64.
Source: Commission services
6.4.
Projections of expenditure on education up to 2050
While education is primarily publicly founded in all Member States, private contributions also
play some role. The share of public education expenditure varies across countries depending
on the specific institutional setting for education and across ISCED levels of education. In
most Member States the share of publicly funded education is close to 100 for basic and
upper-secondary education.76 For tertiary education the shares of publicly funded education
vary somewhat and are generally lower than at lower levels (see Table 6-8). This is taken
account of in the projections, where the share of public funding is kept constant for each
education level.77
76
Public education expenditure is defined as current and capital expenditures on education by local, regional and
national governments, including municipalities. Household contributions are normally excluded.
77
The share of public funding is defined as direct public expenditure as a share of direct public expenditure plus
direct private expenditure, i.e. transfers are not included in the calculation of this share.
174
Table 6-8: Percentage share of education publicly funded (2002).
Country
BE
CZ
DK
DE
EE1
EL
ES
FR
IE
IT
CY
LV
LT
LU1
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
1
Primary
96.6
96.3
98.7
98.2
100.0
92.1
92.9
95.8
96.5
96.4
94.4
97.9
99.8
100.0
93.5
84.5
97.0
97.6
98.1
100.0
90.0
98.1
99.8
100.0
89.7
Low
Secondary
95.9
96.4
95.6
98.0
100.0
94.6
93.8
93.3
97.1
97.4
91.8
98.2
100.0
100.0
93.1
85.9
94.8
96.9
97.9
100.0
90.0
98.8
99.8
99.9
85.0
Upper
Secondary
95.9
99.1
99.0
97.5
100.0
93.4
93.8
90.4
96.0
96.9
92.0
91.9
100.0
100.0
94.6
84.9
87.7
93.6
94.9
99.8
90.7
97.1
98.2
99.9
85.0
Tertiary
86.0
87.5
97.9
91.6
100.0
99.6
76.3
85.7
85.8
78.6
42.0
55.4
93.5
n.a.
78.7
93.9
78.1
91.6
69.7
91.3
76.4
85.2
96.3
90.0
72.0
Data for Estonia and Luxembourg cover only public expenditure.
Source: Commission services based on Eurostat database. The share of publicly funded
education has been estimated as the ratio between total (excluding transfers) public
spending and total direct public and private spending.
Public education expenditure generally consists of direct current and capital expenses of
educational institutions (direct expenditure for educational institutions), support to students
and their families with scholarships and public loans, and/or public subsidies for educational
activities to private institutions or non-profit organisations (transfers to private households
and private institutions). It can thus take the form both of direct public expenditure and of
transfers.
Education expenditure is the product of the number of students and the expenditure per
student. As explained in detail in the methodological report (EPC and COM (2005a))
expenditure per student depends on three main components: (a) gross wages of teaching and
non-teaching staff; (b) pupil/staff ratio; and (c) other cost than wages, both current and
capital. The EPC has agreed that expenditure per student should increase in line with GDP per
worker. This assumption implies that wages follow labour productivity and that the pupil/staff
ratios remain constant, i.e. that any reduction in the number of students due to demographic
factors is accompanied by a similar reduction in the education staff. Transfers are also
assumed to evolve in line with GDP per worker78.
78
Assumptions on labour productivity growth and real GDP growth have been agreed by the AWG and are used
for the whole budgetary exercise. The country appendix presents these assumptions.
175
Table 6-9 presents the main results for the development of expenditure on education to GDP
ratios. It includes direct expenditure and transfers to households and institutions. Projections
show a decrease of public expenditure on education to GDP in all countries. Significant
savings (more than 1 per cent of GDP) are foreseen in Estonia, Ireland, Cyprus, Latvia,
Lithuania, Poland and Slovakia. The overall change in public education expenditure hide
some differences between the four different levels of education, but savings are in general
projected at all levels.
Table 6-9: Total public expenditure on education as a share of GDP (2002-2050)
Level, percentage points
Percentage points change 2002-2050 due to
Lower
Upper
Primary Secondary
Secondary
Tertiary Total1
Country
2002
2010
2030
2050
BE
5.6
5.2
5.0
5.0
-0.2
-0.1
-0.2
-0.1
-0.6
CZ
3.9
3.3
3.0
3.1
-0.1
-0.2
-0.2
-0.2
-0.7
DK
7.6
7.5
7.3
7.5
-0.2
0.1
0.2
-0.2
-0.1
DE2
4.0
3.6
3.3
3.3
-0.1
-0.3
-0.1
-0.2
-0.7
EE
5.3
3.8
3.8
3.6
-0.3
-0.5
-0.5
-0.3
-1.6
EL
3.8
3.1
3.0
3.1
-0.1
-0.1
-0.2
-0.3
-0.7
ES
4.0
3.2
3.0
3.1
-0.1
-0.1
-0.3
-0.4
-0.9
FR3
5.0
4.7
4.5
4.5
-0.1
-0.1
-0.1
-0.1
-0.5
IE
4.3
3.5
3.2
3.1
-0.3
-0.2
-0.3
-0.5
-1.2
IT
4.3
3.9
3.5
3.7
-0.2
-0.1
-0.2
-0.2
-0.7
CY
6.1
5.1
4.3
4.0
-0.7
-0.6
-0.6
-0.2
-2.1
LV
5.2
3.5
3.7
3.5
-0.2
-0.7
-0.6
-0.3
-1.7
LT
5.0
4.2
3.3
3.3
-0.4
-0.8
-0.2
-0.2
-1.7
LU4
3.4
3.1
2.7
2.4
-0.5
-0.2
-0.2
0.0
-1.0
HU
4.6
3.9
3.5
3.8
-0.1
-0.2
-0.3
-0.2
-0.8
MT
4.3
3.7
3.3
3.3
-0.3
-0.4
-0.2
-0.2
-1.0
NL
4.7
4.7
4.6
4.6
-0.1
0.0
0.0
0.0
-0.1
AT
5.1
4.6
4.2
4.1
-0.3
-0.3
-0.2
-0.2
-1.0
PL
5.2
3.9
3.0
3.1
-0.7
-0.4
-0.6
-0.4
-2.0
PT
5.3
4.7
4.5
4.8
0.0
-0.1
-0.2
-0.2
-0.5
SI
5.4
4.6
4.7
4.9
0.1
-0.2
-0.3
-0.1
-0.5
SK
3.8
3.0
2.2
2.4
-0.2
-0.4
-0.5
-0.3
-1.4
FI
6.0
5.6
5.4
5.3
-0.2
-0.1
-0.2
-0.3
-0.8
SE
7.2
6.7
6.6
6.4
-0.3
-0.1
-0.2
-0.1
-0.8
UK5
4.6
4.2
4.1
4.0
-0.2
-0.2
-0.2
-0.1
-0.7
1
Discrepancies are due to rounding.
2
Data do not include spending (around 0.25 of GDP) at the workplace for combined workplace and school
education as well as similar expenditure by "Bundesagentur für Arbeit".
3
GDP includes over-sea Departments.
4
Data cover only spending up to ISCED level 3 and only public spending in public institutions.
5
The expenditure ratio is calculated using the calendar definition of GDP.
Source: European Commission services based on Eurostat data and National Statistic Offices.
6.5.
Decomposition of the changes in the expenditure shares
Table 6-10 compares the percentage change in education expenditure as a share of GDP to the
percentage changes in the young-age population (defined as aged 5-25), the total number of
students and the share of students in the working-age population. The table shows that the
correspondence between the change in the young-age population and the change in the
number of students are generally high. However, there are some clear exceptions. Two
176
possible explanations are changes in enrolment from 2002 to 2003 and developments in the
labour market leading to slight changes in enrolment for single year age-groups, cf. Table 6-6.
In addition, changes in the composition within the age-group 5-25 and the fact that the agegroup 5-25 does not completely correspond to the age-groups enrolled in education influence
the figures.
Two examples can illustrate the effect of changes within the age-group 5-25. The
demographic projections show an increase in the population aged 5-25 in Sweden, but a
significant decrease in the age-groups 10-15. As enrolment is very high in these age-groups,
the result is a decrease in the total number of Swedish students, despite the increase in the 525 age-group. Something similar happens in Cyprus, even if practically all the relevant agegroups will decline. This is because the percentage fall in the population aged 18 and more is
much smaller than for younger children, while enrolment for people aged 18 and more is very
low compared to younger age-groups or to the same age-group in other countries. Low
enrolment among people aged 18 and more implies that developments in the age-group 5-17
are more important for the future number of students than developments in the age-group 18
and over. This explains why the larger fall in the number of children 17 and under heavily
influences the expected total number of students.
Denmark can illustrate the latter mechanism: A significant number of Danish students are 26
years or older. Combined with large expected reductions in the size of these age groups, this
leads to people aged 26 or more making up 40 per cent of the expected fall in students. This
explains how the fall in the number of students (7.8) can be so much larger than the fall in the
number of people aged 5-25 (4.4). The age-group chosen to illustrate the demographic
developments is in other words less relevant in Denmark than in most other countries.
As education expenditure is measured as a share of GDP, an increasing or decreasing size of
the working-age population will, for given labour market participation shares, greatly
influence the figures. This can be seen in the table as a large difference between the
developments in the total number of students and the students to working-age populationratio. For a number of countries, developments in the latter variable correspond more closely
with developments in the total expenditure ratio, but for other countries the opposite is the
case.
177
Table 6-10: Education expenditure as a share of GDP compared to the young-age
population (defined as aged 5-25), the total number of students and the share of students
over population aged 15-64. Percentage changes 2002-2050
BE
CZ
DK
DE
EE
EL
ES
FR
IE
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
SI
SK
FI
SE
UK
Young age
population
-9.6
-42.2
-4.4
-27.1
-40.8
-30.8
-28.8
-5.5
-3.5
-25.7
-14.2
-43.3
-45.0
36.4
-34.9
-7.6
0.4
-22.6
-47.1
-28.4
-33.1
-48.5
-15.8
2.6
-12.1
Total number
of students
-10.5
-39.8
-7.8
-26.7
-42.5
-26.9
-25.4
-6.1
0.0
-23.9
-17.4
-45.2
-44.8
31.3
-31.9
-7.6
-2.6
-25.7
-47.8
-25.6
-28.1
-46.8
-17.9
-5.2
-13.7
Students to
working-agepopulation-ratio
-3.8
-14.1
0.6
-9.1
-21.4
-7.3
-8.7
-3.1
-16.7
-0.8
-34.1
-21.3
-25.5
-0.6
-8.5
-19.5
0.5
-13.5
-29.0
-5.8
-5.6
-27.1
-5.4
-9.8
-11.5
Total expenditure in
education
-11.2
-19.3
-1.2
-18.0
-31.0
-18.4
-22.5
-9.6
-27.7
-15.1
-34.1
-32.8
-33.3
-28.5
-16.6
-23.9
-1.7
-19.5
-39.6
-9.8
-10.0
-36.5
-12.5
-11.0
-14.5
Source: Commission services
A more detailed decomposition is therefore necessary to explain the developments in
education expenditure. Table 6-11 sheds light on the different explanatory factors. The table
indicates how much education expenditure would change from 2002 to 2050 if only one of
the decisive factors change. The decomposition used is the following:
(1)
POP5 − 25 POP15 −64 ES
EDU
S
=
*
*
*
GDP POP5 − 25 POP15 −64
N
π
where
EDU/GDP is total public expenditure in education as a share of GDP, S is the number of
students, POP5-25 is the population aged 5-25, POP 15 − 64 is the working-age population, N is
employment, ES is expenditure per student and π is GDP per worker. Each fraction is
represented by a column in Table 6-11. For example, the first column is calculated by
assuming that the share of students to the population aged 5-25 changes as in the projections,
POP5 − 25 POP15 −64 ES
while all other factors (
*
*
) remain at the 2002 level.
POP15 −64
N
π
178
The table shows that in this case education expenditure in the Czech Republic would increase
by 0.2 percentage points.
The first column shows the effect of the changes in the ratio between total number of students
and the total population aged 5-25. As mentioned above, changes in this ratio can be due to
changes in actual enrolment from 2002 to 2003, different demographic developments in
single year age-groups within 5-25 years or above, or to labour market influence on enrolment
rates. The effect of this factor varies between countries, but it is never very large.
The effect of a smaller share of young people relative to the working-age population is shown
in the second column. Not surprisingly, this effect pulls expenditure downwards in most
countries, and stands out as the most significant contribution to lower education expenditure
overall.
The third column illustrates the importance of the change in the share of employed people to
the working-age population. The higher employment rates for individual age groups that
result from the applied cohort approach, point to higher GDP and therefore reduced education
expenditure as a share of GDP. At the same time, an older workforce points in the opposite
directions, but the latter effect is not large enough to outweigh the former. Overall,
developments in employment point in the direction of reduced education expenditure
measured as a share of GDP.79
Expenditure per student is assumed to develop in line with GDP per worker. This means that
for each education level, column four shall by definition be zero. However, as the cost level
differs between different education level and their relative importance change within the
projection period, this is not necessarily the case for the average cost level. The table shows
that the development in the average cost level have small effects in all countries.
The last column shows the total change in education expenditure over the period 2002 to
2050. This is not always equal to the sum of the first four columns due to multiplicative
effects. However, in most cases the difference is small.
79
The figures for Luxembourg are related to a continuous increase in labour input over the projection period.
This must be seen in relationship with the assumptions on cross-border workers.
179
Table 6-11: Decomposition of the change in the education expenditure to GDP-ratio.
Percentage point contribution from different factors. 2002-2050
Inverse of
Difference 2002Cost level4
employment3
2050
-0.1
-0.2
-0.5
0.1
-0.6
BE
0.2
-0.7
-0.2
0.0
-0.7
CZ
-0.3
0.3
-0.2
0.0
-0.1
DK
-0.1
-0.2
-0.4
0.1
-0.7
DE
-0.1
-1.0
-0.5
-0.1
-1.6
EE
0.2
-0.5
-0.3
-0.2
-0.7
EL
0.2
-0.5
-0.6
0.0
-0.9
ES
0.0
-0.1
-0.4
0.1
-0.5
FR
0.2
-0.8
-0.5
-0.1
-1.2
IE
0.1
-0.1
-0.6
0.0
-0.7
IT
-0.2
-1.9
-0.2
0.2
-2.1
CY
-0.2
-1.0
-0.7
-0.1
-1.7
LV
0.0
-1.3
-0.6
0.1
-1.7
LT
-0.1
0.1
-1.0
0.1
-1.0
LU
0.2
-0.6
-0.4
0.0
-0.8
HU
0.0
-0.8
-0.3
0.1
-1.0
MT
-0.1
0.2
-0.3
0.2
-0.1
NL
-0.2
-0.5
-0.4
0.0
-1.0
AT
-0.1
-1.4
-0.7
-0.1
-2.0
PL
0.2
-0.5
-0.3
0.1
-0.5
PT
0.4
-0.7
-0.3
0.0
-0.5
SI
0.1
-1.1
-0.5
0.0
-1.4
SK
-0.2
-0.2
-0.5
0.1
-0.8
FI
-0.5
-0.2
-0.2
0.2
-0.8
SE
-0.1
-0.5
-0.2
0.0
-0.7
UK
1
Enrolment is defined as total number of students over the population aged 5-25 years.
2
The young share is defined as the population aged 5-25 years over population aged 15-64.
3
The inverse of employment is defined as the population aged 15-64 over employment.
4
The cost level is defined as the expenditure per student over GDP per worker
Source: Commission services
Enrolment1
6.6.
Young share2
A word of caution
The projections of reduced education expenditure depend on a number of variables. Most
importantly, no underlying trend neither in enrolment rates nor in expenditure per student
relative to GDP per worker is included. Unlike some of the other elements of the age-related
expenditure exercise, the projections thus illustrate only the effect of demographic
developments on education expenditure, and do not comprise any estimation of nondemographic drivers other than labour market developments. Regarding enrolment, this in
some cases do not reflect national expectations of increasing enrolment rates as a result of
implemented or planned legislation or other policies.
As shown in Graph 6-2, most Member states have already seen a decline in the number of
people aged 5-2580. In particular, significant reductions have been recorded in some south
European countries and in some recently acceded Member States, with a decline of around 15
percentage points or more in the Czech Republic, Spain, Italy, Latvia, Portugal and Slovenia
80
The only significant increase was registered in Cyprus.
180
over the period 1990-2003. Still, there was no marked downward trend in education
expenditure ratios (see Table 6-12).
This illustrates that factors other than demographic developments have been important to the
historical developments of education expenditure. The projected savings are conditional on
these factors not continuing to point in an upward direction. This is far from certain neither
for costs per student nor for enrolment rates. First, emphasis on the quality of education and
difficulties in adjusting downwards the number of teachers as the number of students fall,
could point in the direction of increased costs per student. Second, some Member States have
either planned or implemented policies to move students through the education system more
rapidly. However, stated policy priorities, e.g. related to the Lisbon agenda, mostly emphasize
the importance of increasing enrolment rates. Increased income levels may also lead to more
people being able and willing to spend a larger part of their life on education. Together with
some information available on actual enrolment in 2004, this indicates that average actual
enrolment rates in the future may be more likely to be higher than this exercise projects than
lower. Finally, education is largely an investment in human capital, though also partly a
consumption good. Enrolment increases would therefore in addition often be beneficial also
from a public finance point of view, once effects on productivity and labour market
participation is taken into account.
A detailed analysis of these factors has been beyond the scope of this exercise. The important
point is to note that the projections should in no way be taken to imply that large and easy
savings can be expected for public finances due to developments in the educational sector.
Graph 6-2: Rate of change of population aged 5-25 between 1990 and 2003. Percentage
points
20
CY
15
10
5
SE
0
-5
-10
BE
DK
NL
FR
DE
SK
UK
AT
LT HU
GR
-15
FI
PL
IE
LV
CZ
-20
SI
PT
ES
-25
IT
-30
Source: Commission services based on New Chronos Eurostat database.
Note: Due to lack of data in New Chronos Eurostat database, Estonia and Malta are not represented in the graph.
For Cyprus the graph reports the rate of change between 1993 and 2003.
181
Table 6-12: Expenditure on education as share of GDP. EU15. 1990-2003
Education expenditure/GDP
BE
DK
DE
EL
ES
FR
IE
IT
NL
AT
PT
FI
SE
UK
Early ‘90s (90-94)
Late ’90 (95-99)
Early ’00 (00-03)
6.4
7.5
4.3
3.4
n.a.
n.a.
n.a.
5.5
n.a.
n.a.
5.8
7.4
n.a.
4.5
6.3
7.9
4.4
3.3
n.a.
6.2
4.7
5.0
4.9
6.0
6.6
6.8
7.3
4.6
6.2
8.3
4.1
3.3
4.2
6.0
4.3
5.1
4.9
5.8
7.0
6.5
7.3
5.0
Source: European Commission Economic Database, AMECO (COFOG classification)
182
7.
UNEMPLOYMENT BENEFITS
7.1.
Description of the projection methodology
In order to get a comprehensive assessment of the total impact of ageing on public finances,
and to guarantee consistency with the macroeconomic scenario, it was agreed to run
projections for spending on unemployment benefit spending as part of the overall age-related
expenditure projection exercise. In order to assess whether and by how much unemployment
benefit (henceforth UB) expenditure would be affected by projected changes in the
unemployment situation in Member States, a simplified methodology has been used as it was
the case in 2003 exercise.81
Projections have been carried out using the average per-capita unemployment insurance
spending in a base year. In order to avoid that the choice of the base year was overly
conditioned by the cyclicality of labour market conditions and/or possible statistical errors,
the figures for the base year are equivalent to the average of spending over the period 19982002 (last year for which figures are available in Eurostat database). This per capita spending
has been combined with the agreed baseline assumptions on unemployed persons (which are
referred to the projected NAIRU) reported on Table 7-4. This straightforward calculation
implies assuming, under a no-policy change hypothesis, constant replacement rates, duration
of benefit, entitlement conditions, eligibility criteria, take-up rates, and tax structure. Finally,
as it is the case for the pension projections, it also assumes a constant share of wages in the
income distribution over time (that is, the wage per worker grows at the same rate as labour
productivity, i.e. GDP per worker).
This set of “invariance” assumptions can be illustrated by decomposing the total
unemployment benefit spending UB, as follows:
UB = GRR × pcw ×
(1)
UBr
×U
U
where GRR is the gross replacement rate, pcw is per capita wage, UBr is the number of
UBr
recipients (unemployed persons receiving unemployment benefits), and thus the ratio
is
U
W Y
the take-up ratio. Given that per capita wages can also be written as: pcw = × ,
Y L
(where L is employment, Y is GDP and W is total wages)
then UB can be re-written as :
UB = GRR ×
(2)
W Y UBr
× ×
×U
Y L U
where W/Y is the share of wages in the income distribution and Y/L is labour productivity.
81
EPC (2003).
183
UB
W Y UBr
and this can be expressed in terms of
= GRR × × ×
U
Y L U
GDP per worker (or Ypc=Y/L) as follows:
Per capita UB is : UBpc =
(3)
UBpc UB / U
W Y UBr L
=
= GRR × × ×
×
Ypc
Y /L
Y L U
Y
Thus, the total expenditure as percentage of GDP can be expressed as:
UB
W UBr U
= GRR × ×
×
Y
Y
U
L
(4)
Given that L = LF (1-u), where LF = labour force and u = unemployment rate, the ratio (Ut/Lt)
can also be re-written as ut/(1-ut) and:
UB
W UBr
u
= GRR × ×
×
(5)
.
Y
Y
U
(1 − u )
In this formulation, if one assumes no change in both the GRR and the take-up ratio (UBr/U),
and a constant share of wages in income distribution (W/Y), as a result of the assumption that
wages grow at the same rate as labour productivity, only changes in the unemployment rate
(or the ratio of unemployed to employed persons, U/L) will drive the change over time of
unemployment benefit spending.
This methodology generates projections of UB expenditure, expressed as a share of GDP,
where average expenditure per head grows at the same rate as GDP per worker in each
projection year. Thus, the basic approach applied to run projections for UB expenditure (as
percentage of GDP) is the following (a formal illustration of the methodology is presented in
Annex 8):
•
82
estimate the average amount of UB received by each unemployed person (and as
percentage of GDP per worker) in the base year (Ubpcb/Ypcb). This was done by
dividing the average amount of UB expenditures (as % of GDP) over the period 1998200282 by the average of the ratio unemployed/employed persons over the same period
(see Table 7-3)83. In the absence of any alternative and reasonable assumption on the
future number of UB beneficiaries (which is the result of entitlement and eligibility
rules that affect coverage, take up rates, and so on) and the average duration of
unemployment spells, the calculation assumes that all these elements remain
unchanged. This approximation is neutral and does not lead to a systematic bias in the
projections of benefit spending. In order to guarantee the comparability of projections
across countries, standardised figures provided by EUROSTAT –Social protection
Expenditure (instead of country-specific figures coming from national databases) are
used. Specifically, we used the two main components (i.e. “kind of benefits”) of the
Eurostat definition of social protection spending related to unemployment, that is
benefit spending for “Partial unemployment” and “Full unemployment”. A breakdown
Latest available figures provided by EUROSTAT-Social Protection Expenditure, see table 2.
83
In the case of Germany, Belgium and Luxembourg, figures used are not the original labour force projections calculated by
the Commission, but are figures converted by Member States, in agreement with the AWG, in national-account equivalent
(or in line with administrative concepts). This is consistent with what has been done for projecting pension expenditure and
other age-related spending. See EPC-EC-DG ECFIN(2005), Carone (2005).
184
by kind of benefit of the total social protection expenditure related to unemployment84
in 2002 is provided in Table 7-2
•
for each projection year, the ratio unemployment benefit /GDP per head in the base
year (from the step above - see results in Table 7-3) has been multiplied by the
corresponding expected ratio between the future number of unemployed persons and
employed persons (U/L) for each country and each of the year of projections (basic
figures are reported in Table 7-5). The projections of employed and unemployed
persons are those referred to the “current policy” macroeconomic scenario (see Table
7-4 and Table 7-5). This generates projections of UB spending, expressed as a share of
GDP85.
84
In the Eurostat-ESSPROS database, the category “unemployment” also includes spending on placement services and job
search assistance, early-retirement benefit for labour market reasons, vocational training, lump sum benefit redundancy
compensation, mobility and resettlement benefits. As a general rule, early retirement and pre-retirement benefits to older
workers are included in the projections on pension expenditures.
85
The projection does not take into account that unemployment benefits are subject to income tax, so that after tax UB
spending as % of GDP is lower. This should be taken into account when assessing fiscal sustainability. Still, given the
assumption of invariant tax structure, results in terms of changes in the after-tax UB spending (as % of GDP) over the
projection period would be broadly the same as those obtained by using before- tax spending as in this projection exercise.
185
Table 7-1 - Social protection expenditure as % of GDP: Unemployment
(2002)
Kind of benefit
Social protection benefits:unemployment (a+b
Cash benefits (a)
Full unemployment benefits
Partial unemployment
Placement services and job search assistance
Early retirement benefit for labour market reasons
Periodic benefit vocational training
Other periodic cash benefits
Lump sum cash benefits
Lump sum benefit vocational training
Lump sum benefit redundancy compensation
Other lump sum cash benefits
Benefits in kind (b)
Mobility and resettlement benefits
Vocational training
Other benefits in kind
* 2001
EU15 EU12
B
CZ
DK
DE
EE*
EL
ES
F
IE
I
LV*
LT*
L
HU
MT
NL
AT
PL*
PT
SI
SK
FI
SE
UK
2.7
2.6
2.5
2.2
0.2
:
1.6
0.5
2.7
2.4
2.2
2.2
1.3
1.1
0.4
0.4
0.5
:
0.1
:
0.8
0.8
0.6
0.5
1.2
1.1
1.4
1.4
1.5
1.1
0.9
:
0.9
0.9
0.8
0.7
1.8
1.6
1.9
1.8
3.2
3.2
0.7
0.6
0.8
0.6
2.5
2.3
1.7
1.4
0.9
0.8
1
0
0
0.2
0.2
0
0.2
0
0.2
0
1.1
0
0
0.2
0.2
0
0.2
0
0.1
0
1.9
0.4
0
0.4
0.1
0.4
0
0
0
0
0.2 1.3 1.2 0.1 0.4 1.5 1.5 0.8 0.3 0.4 0.1 0.3 0.3 1 1.4 0.8 0.4 0.8 0.3 0.3
:
:
0 0..1 0.1 0
0
:
0
:
:
0
:
:
0
:
:
0
0
:
: 0.1 0
:
0
0
: 0.1 0
:
:
0
0
0
0 0.1 :
0 0.1 0.1
0
: 0.3 : 0.1 0 0.2 : 0.1 :
: 0.2 0.1 :
0 0.1 0.5 0 0.2 0
0 1.3 0.5 :
0
0 0.2 0.2 0
:
:
0
:
0
0 0.1 :
0
0
:
:
:
0
:
0 0.1 :
:
0
:
: 0.2 0.1 0.1 0
0
:
0
0
:
0.4 0 0.1 : 0.1 0.7 0.3 0.1 0
:
: 0.1 0.1 :
0 0.1 :
0 0.1 0.3
:
0
:
:
0
:
:
0
0
:
: 0.1 :
:
0
:
:
0
:
:
0.2 : 0.1 :
0 0.6 0.3 0.1 0
:
:
0 0.1 :
0
0
:
0
: 0.3
0.2 0
0
:
0
0
0
:
0
:
:
0
0
:
0 0.1 :
0 0.1 0
1.6
0
0.1
0.5
0.1
0
0
0
0
0
1
0
0.1
0
0.3
:
0.1
:
0.1
:
0.5
0
0
0
0.1
0
0.3
0
0.3
0
0.2
0.2
0.1
0
0.1
0.3
:
1.1
0.3
0
0.2
0
:
:
0
0.1
0
0
0.4
:
0
0.1
0.1
0.2
0.3
0.1
0
0
0.1 0.1
0
0
0
0
:
:
0
0
:
:
:
0.1
0.2
0
:
:
:
0.1 0
0.9 0.3
0.1 0
:
:
0
:
0.1
0
0
0
0
:
0.1
:
:
:
:
0
0
0
:
0.1
:
:
0
0
0
0
0
0
0.1
0.3
:
:
:
0
0
0
:
0
0
:
0
:
Source: Eurostat-Social protection expenditures database (ESPROS)
NB: Early retirement benefits are, as a general rule included in the pension projections.
0
0
0
0.1 0.2 0.1
0
0
0
Table 7-2 – Unemployment benefit spending, as % of GDP
(Full + partial unemployment benefits)
Country
Belgium
Denmark
Germany
Greece
Spain
France
Ireland
Italy
Luxembourg
Netherlands
Austria
Portugal
Finland
Sweden
United Kingdom
Cypros
Czech Republic
Estonia
Hungary
Lithuania
Latvia
Malta
Poland
Slovak Republic
Slovenia
EU-25
EU15
EU12
EU10
aver. 1998-2002
1998
1999
2000
2001
2002*
2.20
1.42
1.16
0.42
1.46
1.30
0.92
0.34
0.22
1.50
0.76
0.72
1.82
1.38
0.42
0.39
0.24
0.10
0.30
0.16
0.46
0.94
0.40
0.44
0.54
2.3
1.7
1.2
0.5
1.6
1.3
1.3
0.4
0.2
1.9
0.8
0.7
2.2
1.8
0.4
0.4
0.2
0.1
0.3
0.2
0.5
0.9
0.4
0.5
0.8
2.2
1.4
1.2
0.4
1.4
1.3
1
0.4
0.2
1.6
0.8
0.7
2
1.6
0.4
0.4
0.3
0.1
0.3
0.2
0.5
1
0.4
0.6
0.7
2.1
1.4
1.1
0.4
1.4
1.2
0.8
0.3
0.2
1.3
0.7
0.7
1.7
1.4
0.3
0.4
0.3
0.1
0.3
0.2
0.5
0.9
0.4
0.5
0.5
2.1
1.3
1.1
0.3
1.4
1.2
0.7
0.3
0.2
1.3
0.7
0.7
1.6
1.1
0.5
0.3
0.2
0.1
0.3
0.1
0.4
0.9
0.4
0.3
0.4
2.3
1.3
1.2
0.5
1.5
1.5
0.8
0.3
0.3
1.4
0.8
0.8
1.6
1
0.5
0.4
0.2
0.1
0.3
0.1
0.4
1
0.4
0.3
0.3
0.99
1.01
1.10
0.36
1.1
1.1
1.2
0.4
1.0
1.0
1.1
0.4
0.9
0.9
1.0
0.4
0.9
0.9
1.0
0.3
1.0
1.0
1.2
0.3
Source: Eurostat-Social protection expenditures database (ESPROS).
* Estonia, Latvia, Lithuania and Poland: 2001
Table 7-3 Unemployment benefit spending per unemployed, as % of GDP per worker
(yubpc)
Country
Belgium
Denmark
Germany
Greece
Spain
France
Ireland
Italy
Luxembourg
Netherlands
Austria
Portugal
Finland
Sweden
United Kingdom
Cypros
Czech Republic
Estonia
Hungary
Lithuania
Latvia
Malta
Poland
Slovak Republic
Slovenia
EU-25
EU15
aver. 1998-2002
1998
1999
2000
2001
2002*
14.4
27.5
13.5
3.3
9.3
11.6
16.6
3.9
10.2
46.3
18.2
14.4
16.3
20.2
7.2
8.2
2.8
0.8
4.2
0.9
2.9
13.0
2.3
1.285**
7.1
14.2
32.0
12.5
3.9
7.0
9.4
15.3
2.9
7.9
41.1
13.8
12.4
16.9
18.1
6.0
6.7
2.9
0.9
3.1
1.3
3.0
12.9
3.5
3.5
9.8
14.1
23.5
13.7
2.8
7.5
9.5
16.7
3.1
8.6
42.4
20.4
14.0
17.5
19.2
6.2
8.0
3.1
0.8
4.0
1.1
3.0
14.3
2.8
3.1
8.5
14.2
28.8
13.9
3.1
8.6
10.5
17.4
2.5
9.9
42.7
18.9
15.7
15.5
23.8
5.1
7.4
3.1
0.6
4.4
1.0
2.9
12.8
2.0
2.2
6.8
14.4
26.7
13.8
2.4
11.8
12.7
16.9
2.8
10.6
56.4
18.6
15.8
15.8
21.3
9.4
7.6
2.2
0.7
4.9
0.5
2.6
11.9
1.8
1.25
5.9
15.0
26.7
13.5
4.3
11.5
15.7
16.8
3.4
13.9
49.2
19.3
14.2
15.9
18.5
9.2
11.4
2.5
0.9
4.8
0.6
2.9
13.3
1.6
1.31
4.4
8.8
10.0
10.2
2.4
9.6
11.5
11.5
2.0
10.2
12.2
12.4
1.9
9.5
9.5
9.3
10.7
9.7
9.9
Euro area
10.8
9.6
10.0
EU10
2.5
3.5
3.1
Source: Eurostat-Social protection expenditures database (ESPROS)
* Estonia, Latvia, Lithuania and Poland: 2001
** Average 2001-2002
188
Table 7-4 –Unemployment rate – (AWG baseline scenario)
1998
13.9
5.0
9.9
11.4
18.7
12.1
7.8
12.0
2.9
4.4
5.5
5.4
11.5
9.0
6.3
5.5
6.5
9.7
8.9
13.6
14.2
6.5
10.2
12.6
7.6
10.3
10.3
9.8
Country
Belgium
Denmark
Germany
Greece
Spain
France
Ireland
Italy
Luxembourg
Netherlands
Austria
Portugal
Finland
Sweden
United Kingdom
Cypros
Czech Republic
Estonia
Hungary
Lithuania
Latvia
Malta
Poland
Slovak Republic
Slovenia
EU25
EU15
EU10
2001
12.6
4.6
7.8
11.0
10.6
8.6
4.0
9.6
2.1
2.3
3.6
4.2
9.2
4.9
5.0
4.1
8.2
12.8
5.8
17.7
13.2
7.0
18.6
19.3
6.3
8.8
7.6
14.7
2002
13.3
4.6
8.6
10.5
11.5
8.7
4.5
9.1
3.1
2.8
4.0
5.3
9.2
5.1
5.2
3.2
7.4
10.5
5.8
13.9
12.2
7.0
20.3
18.7
6.4
9.1
7.9
15.1
2003
14.0
5.5
9.5
9.8
11.6
9.0
4.8
8.9
3.7
3.7
4.3
6.7
9.2
5.7
5.1
4.4
7.9
10.3
5.9
12.5
10.7
7.6
20.1
17.6
6.8
9.3
8.3
14.8
2004
13.7
5.3
9.2
9.3
10.8
9.3
4.3
8.4
3.8
3.7
4.2
6.2
8.5
5.3
4.9
4.2
7.8
9.6
5.5
11.9
9.8
8.4
19.0
16.9
6.3
9.0
8.0
14.1
2005
13.4
4.9
9.0
9.3
10.4
9.1
4.0
8.2
4.0
3.5
3.9
6.0
8.0
5.0
4.8
4.0
7.8
9.1
5.3
11.2
9.1
8.5
18.7
16.7
6.0
8.8
7.8
13.8
2010
12.4
4.3
8.1
8.6
8.7
8.3
3.4
7.3
4.2
3.2
3.4
5.6
6.8
4.3
4.6
4.2
7.3
7.8
4.8
8.9
7.6
8.3
15.8
15.2
5.5
7.8
7.0
12.0
2015
11.4
4.3
6.5
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
12.9
12.5
5.5
6.7
6.1
10.0
2020
11.2
4.3
6.5
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
9.9
9.7
5.5
6.4
6.1
8.3
2025
11.1
4.3
6.5
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
7.0
7.0
5.5
6.2
6.1
6.6
2050
10.9
4.3
6.5
7.0
7.0
7.0
3.4
6.5
4.2
3.2
3.4
5.6
6.5
4.3
4.6
4.2
6.5
7.0
4.8
7.0
7.0
7.0
7.0
7.0
5.5
6.1
6.0
6.6
2003-2025
-2.9
-1.2
-3.0
-2.8
-4.6
-2.0
-1.4
-2.4
0.6
-0.5
-0.9
-1.1
-2.7
-1.4
-0.5
-0.2
-1.4
-3.3
-1.2
-5.5
-3.7
-0.6
-13.1
-10.6
-1.2
-3.2
-2.2
-8.3
-1.7
-2.9
Belgium*
8.2
7.9
7.7
7.0
6.5
6.5
6.5
6.5
Germany*
9.9
9.5
9.4
8.5
7.0
7.0
7.0
7.0
Source: Commission services
Note: For Germany and Belgium figures used in the projections refers to national account and administrative
concepts respectively.
* Figures based on labour force projections
Table 7-5 –Unemployment/Employment ratio (U/L)
% change
2005-15 2005-50
2002
2005
2006
2007
2008
2009
2010
2015
2020
2025
2030
2050
Belgium
0.15
0.15
0.15
0.15
0.15
0.15
0.14
0.13
0.13
0.12
0.12
0.12
-17%
-21%
Denmark
0.05
0.05
0.05
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
-14%
-14%
Germany
0.09
0.09
0.09
0.09
0.09
0.09
0.08
0.07
0.07
0.07
0.07
0.07
-29%
-30%
Greece
0.12
0.10
0.10
0.10
0.10
0.10
0.09
0.08
0.08
0.08
0.08
0.08
-27%
-27%
Spain
0.13
0.12
0.11
0.10
0.10
0.10
0.10
0.08
0.08
0.08
0.08
0.08
-35%
-35%
France
0.10
0.10
0.10
0.10
0.10
0.09
0.09
0.08
0.08
0.08
0.08
0.08
-25%
-25%
Ireland
0.05
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
-15%
-15%
Italy
0.10
0.09
0.09
0.08
0.08
0.08
0.08
0.07
0.07
0.07
0.07
0.07
-22%
-22%
Luxembourg
0.02
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.02
0.02
4%
-18%
Netherlands
0.03
0.04
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.03
0.03
-8%
-8%
Austria
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
-13%
-13%
Portugal
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
-8%
-8%
Finland
0.10
0.09
0.08
0.07
0.07
0.07
0.07
0.07
0.07
0.07
0.07
0.07
-20%
-20%
Sweden
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
-14%
-14%
United Kingdom
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
-4%
-4%
Cypros
0.03
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
5%
5%
Czech Republic
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.07
0.07
0.07
0.07
0.07
-18%
-18%
Estonia
0.12
0.10
0.09
0.09
0.09
0.09
0.09
0.08
0.08
0.08
0.08
0.08
-25%
-25%
Hungary
0.06
0.06
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
-10%
-10%
Lithuania
0.16
0.13
0.12
0.11
0.11
0.10
0.10
0.08
0.08
0.08
0.08
0.08
-40%
-40%
Latvia
0.14
0.10
0.09
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
-25%
-25%
Malta
0.08
0.09
0.10
0.10
0.10
0.09
0.09
0.08
0.08
0.08
0.08
0.08
-19%
-19%
Poland
0.25
0.23
0.22
0.21
0.20
0.20
0.19
0.15
0.11
0.08
0.08
0.08
-36%
-67%
Slovak Republic
0.23
0.20
0.20
0.20
0.20
0.19
0.18
0.14
0.11
0.08
0.08
0.08
-29%
-63%
Slovenia
0.07
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
-8%
-8%
EU25
0.10
0.10
0.09
0.09
0.09
0.09
0.08
0.07
0.07
0.06
0.06
0.06
-25%
-32%
EU15
0.09
0.08
0.08
0.08
0.08
0.08
0.07
0.06
0.06
0.06
0.06
0.06
-23%
-24%
Eurozone
0.09
0.09
0.09
0.09
0.09
0.08
0.08
0.07
0.07
0.07
0.07
0.07
-26%
-27%
EU10
0.18
0.16
0.16
0.15
0.15
0.14
0.14
0.11
0.09
0.07
0.07
0.07
-31%
-56%
Source: Commission services
Note: For Germany and Belgium figures used in the projections refers to national account and administrative
concepts respectively.
189
7.2.
Results of projections for public expenditure on unemployment benefit
expenditure
The results of calculation, which depend critically upon previous assumptions on working-age
population, labour market participation and unemployment rates, are reported in Table 7-6.
Unemployment benefit spending in the EU25 and EU15 is projected to fall from about 1% of
GDP in 2002-2003 to 0.6% in 2025-2050. This primarily reflects the assumed lower
proportions of unemployed people over the projection period.
Table 7-6- Projections of unemployment benefit spending, as % of GDP
2002
2005
2006
2007
2008
2009
2010
2015
2020
2025
2030
2035
2040
2050
Change in expenditure
(percentage points)
2002-2015 2002-2050
(actual figures)
BE
DK
DE
GR
ES
FR
IE
IT
LU
NL
AT
PT
FI
SE
UK
CY
CZ
EE
HU
LT
LV
MT
PL
SK
SI
2.30
2.23
2.20
2.16
2.13
2.09
2.03
1.85
1.81
1.80
1.77
1.75
1.75
1.76
1.30
1.43
1.33
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.20
1.27
1.24
1.22
1.22
1.17
1.13
0.90
0.89
0.89
0.88
0.89
0.89
0.89
0.50
0.34
0.34
0.34
0.34
0.32
0.31
0.25
0.25
0.25
0.25
0.25
0.25
0.25
1.50
1.07
1.02
0.96
0.96
0.92
0.89
0.70
0.70
0.70
0.70
0.70
0.70
0.70
1.50
1.16
1.14
1.13
1.13
1.09
1.05
0.87
0.87
0.87
0.87
0.87
0.87
0.87
0.80
0.69
0.64
0.59
0.59
0.59
0.59
0.59
0.59
0.59
0.59
0.59
0.59
0.59
0.34
0.40
0.39
0.38
0.38
0.37
0.36
0.32
0.32
0.32
0.32
0.32
0.32
0.32
0.30
0.26
0.27
0.28
0.28
0.28
0.28
0.27
0.27
0.26
0.25
0.24
0.23
0.22
1.40
1.69
1.62
1.54
1.54
1.54
1.54
1.54
1.54
1.54
1.54
1.54
1.54
1.54
0.80
0.74
0.69
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.65
0.80
0.92
0.88
0.85
0.85
0.85
0.85
0.85
0.85
0.85
0.85
0.85
0.85
0.85
1.60
1.42
1.32
1.22
1.22
1.20
1.19
1.14
1.14
1.14
1.14
1.14
1.14
1.14
1.00
1.05
0.98
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.91
0.50
0.36
0.35
0.34
0.34
0.34
0.34
0.34
0.34
0.34
0.34
0.34
0.34
0.34
0.37
0.34
0.33
0.31
0.31
0.31
0.36
0.36
0.36
0.36
0.36
0.36
0.36
0.36
0.20
0.23
0.23
0.23
0.23
0.23
0.22
0.19
0.19
0.19
0.19
0.19
0.19
0.19
0.10
0.08
0.07
0.07
0.07
0.07
0.07
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.30
0.24
0.22
0.21
0.21
0.21
0.21
0.21
0.21
0.21
0.21
0.21
0.21
0.21
0.10
0.11
0.10
0.10
0.10
0.09
0.09
0.07
0.07
0.07
0.07
0.07
0.07
0.07
0.40
0.29
0.27
0.24
0.24
0.24
0.24
0.22
0.22
0.22
0.22
0.22
0.22
0.22
1.00
1.22
1.24
1.27
1.27
1.23
1.18
0.98
0.98
0.98
0.98
0.98
0.98
0.98
0.40
0.54
0.52
0.50
0.48
0.46
0.44
0.34
0.26
0.18
0.18
0.18
0.18
0.18
0.30
0.26
0.25
0.25
0.25
0.24
0.23
0.18
0.14
0.10
0.10
0.10
0.10
0.10
0.30
0.45
0.43
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
0.41
EU25
EU15
Euro area
EU10
1.01
0.90
0.88
0.85
0.85
0.82
0.79
0.68
0.64
0.61
0.61
0.61
0.61
0.61
1.04
0.89
0.87
0.85
0.84
0.82
0.80
0.69
0.68
0.68
0.68
0.68
0.68
0.68
1.16
0.99
0.97
0.94
0.94
0.91
0.88
0.74
0.73
0.73
0.73
0.73
0.73
0.73
0.33
0.41
0.40
0.38
0.37
0.36
0.35
0.28
0.23
0.18
0.18
0.18
0.18
0.18
-0.45
-0.08
-0.30
-0.25
-0.80
-0.63
-0.21
-0.02
-0.03
0.14
-0.15
0.05
-0.46
-0.09
-0.16
-0.01
-0.01
-0.04
-0.09
-0.03
-0.18
-0.02
-0.06
-0.12
0.11
-0.54
-0.08
-0.31
-0.25
-0.80
-0.63
-0.21
-0.02
-0.08
0.14
-0.15
0.05
-0.46
-0.09
-0.16
-0.01
-0.01
-0.04
-0.09
-0.03
-0.18
-0.02
-0.22
-0.20
0.11
-0.33
-0.36
-0.42
-0.04
-0.40
-0.37
-0.43
-0.15
Source: Commission services
In 2050, as a straightforward outcome of previously projected demographic and labour market
changes (see Table 7-4 and Table 7-5), overall levels of UB spending would range from about
1.8% of GDP in Belgium to 0.2 (in Greece, Luxembourg Czech Republic, Hungary, Latvia,
and Poland) and a minimum of 0.07% in Lithuania. Compared to the starting year of
calculation, the percentage change in the UB spending is somewhat high in some countries
(higher than 60% in Poland and Slovakia, about 40% in Spain and Lithuania, 30% in
Germany, Estonia, Latvia), reflecting the projected strong fall in the unemployment rates.
On the other hand, it is also worth noting that the impact of the assumed demographic/labour
market changes on expenditure on unemployment benefits is relatively small when compared
to projected effects on pension and health care spending. When compared to 2002, the
maximum projected reduction in the unemployed benefit spending is about 0.8 percentage
points of GDP in Spain, followed by France, Belgium and Finland (0.5-0.6 p.p.).
Among the new Member States, Poland is projected to record the biggest reduction in
unemployment benefit spending (-0.22 percentage points), because of the assumed strong
drop in the unemployment rate, from 19.9% in 2003 to 7% in 2025. Yet, the absolute impact
190
on the expenditure appears to be relatively limited, reflecting a lower initial per capita
spending for unemployed allowances.
To conclude, figures provided by this projection exercise are useful in indicating some broad
orders of magnitude of future public spending for unemployment benefits associated with
assumed trends in population and labour market functioning. These figures should be used
with caution. This is not only because of the high degree of uncertainty which always
surround projections over a half-century, but also because the projection exercise does not
incorporate the complex institutional details of the functioning of the unemployment benefit
schemes in each Member State.
191
REFERENCES
Ahn N., J.R.García, J.A.Herce (2005), Demographic Uncertainty and Health Care
Expenditure in Spain, FEDEA, Documento de Trabajo 2005-07.
Anderson G. and P.Hussey (2000), Population Aging: A comparison Among Industrialized
Countries, Health Affairs, No.19(3), pp.191-203.
Arpaia A, D. Costello, G. Mourre and F. Pierini (2005), “Tracking labour market reforms in
the EU Member States: an overview of reforms in 2004 based on the LABREF database”,
European Commission Economic paper N° 239, December 2005, available at:
http://europa.eu.int/comm/economy_finance/publications/economicpapers_en.htm
Arpaia A, and G. Mourre (2005), “Labour market institutions and labour market
performance: A survey of the literature”, European Commission Economic paper N° 238,
December 2005, available at:
http://europa.eu.int/comm/economy_finance/publications/economicpapers_en.htm
Australian Government, Productivity Commission (2004), Economic Implications of an
Ageing Australia. Draft Research Report, available at:
http://www.pc.gov.au/study/ageing/draftreport/index.html
Bac C. (2004), Les déterminants macro-économiques des dépenses de santé : comparaison
entre quelques pays développés. Annex to : Alain Vasselle, Projet de loi relatif à l'assurance
maladie. Rapport n° 424 (2003-2004), fait au nom de la commission des affaires sociales,
déposé le 21 juillet 2004, available at: http://www.senat.fr/rap/l03-424-1/l03-424-112.html
Bac C. and D.Balsan (2001), Modélisation des dépenses d’assurance maladie, Document de
travail, No.19, Direction de la recherche, des études, de l’évaluation et des statistiques
DREES.
Barros P.P. (1998), The black box of health care expenditure growth determinants, Health
Economics, Vol.7(6), pp.533-544.
Batljan I. and M.Lagergren (2000), Will There be a Helping Hand? Macroeconomic
scenarios of future needs and costs of health and social care for the elderly in Sweden, 200030. Annex to The Long-Term Survey 1999/2000, Stockholm.
Batljan I. and M.Lagergren (2004), Inpatient/outpatient health care costs and remaining
years of life. Effect of decreasing mortality on future acute health care demand, Social
Science and Medicine, Vol.59, pp.2459-2466.
Batljan I. (2005), Demographics and demand for care. How to incorporate death-related
costs in long-term budgetary projections of health care and long-term care?, Presentation in
the framework of the Visiting Fellows Programme, European Commission, 12 April 2005.
Berthelot J.-M. (2004), Health-adjusted Life Expectancy (HALE), in: J.-M.Robine, C.Jagger,
C.D.Mathers, E.M.Crimmins, R.M.Suzman (eds.), Determining Health Expectancies, John
Wiley and Sons, Chichester, pp.235-246.
192
Bjornerud S. and J.Oliveira Martins (2005), Disentangling demographic and nondemographic drivers of health spending: a possible methodology and data requirements,
presentation at the Joint EC/OECD Workshop, 21-22 February 2005, Brussels.
The Boards of Trustees, Federal Hospital Insurance and Federal Supplementary Medical
Insurance Trust Funds (2004), 2004 Annual Report of the Boards of Trustees of the Federal
Hospital Insurance and Federal Supplementary Medical Insurance Trust Funds, Washington.
Bokhari F.A.S. (2001), Managed Care and the Adoption of Hospital Technology: the Case of
Cardiac Catherization, HEW 0110001, Economics Working Paper Archive at WUSTL.
Börsch-Supan A., A Brugiavini, H. Jürges, J. Mackenbach, J. Siegrist and Weber G. Editors
(2005), ‘Health, ageing and retirement in Europe: first results from the Survey of health,
Ageing and Retirement In Europe’, SHARE project through the 5th Research Framework
programme of the European Union, Mannheim Research Institute for the Economics of Aging
(MEA).
Brody J.A., S.Frells, T.P.Miles (1992), Epidemiological issues in the developed world, in
J.G.Evans, T.F. Williams (eds.), Oxford Textbook of Geriatric Medicine, Oxford Medical
Publications, pp.14-20, Oxford.
Burniaux J., M., R. Duval and F. Jaumotte (2003), ‘Coping with ageing: a dynamic approach
to quantify the impact of alternative policy options on future labour supply in OECD
countries’, OECD Economic Department WP. N. 371; and OECD (2003), ‘Labour force
participation of groups at the margin of the labour market: past and future trends and policy
challenges’, Working Party N° 1 on Macroeconomic and Structural Policy Analysis,
ECO/CPE/WP1(2003)8.
Busse R., C.Krauth and F.W.Schwartz (2002), Use of acute hospital beds does not increase as
the population ages: results from a seven year cohort study in Germany, Journal of
Epidemiology and Community Health 2002, vol.56, pp.289-293.
Busse R., G.Wurzburg, M.Zappacosta (2003), Shaping the Societal Bill: past and future
trends in education, pensions and healthcare expenditure, Futures, Vol.35, pp.7-24.
Caisse Nationale de l’Assurance Maladie des Travailleurs Salariés (2003), Le viellissement de
la population et son incidence sur l’évolution des dépenses de santé, Des tendances de fond
aux mouvements de court terme. Point de conjoncture, no.15, Juillet 2003.
Carone G., D.Costello, N. Diez Guardia, G. Mourre, B. Przywara, A. Salomäki (2005), “The
economic impact of ageing populations in the EU25 Member States”, European Commission
Economic paper N° 236, December 2005, available at:
http://europa.eu.int/comm/economy_finance/publications/economicpapers_en.htm
Carone G., C.Denis, K. Mc Morrow, G. Mourre, W. Röger (2006), “Long-term labour
productivity and GDP projections for the EU25 Member States: a production function
approach”, in European Commission Economic paper, forthcoming.
Carone G. (2005), “Long-term labour force projections for the 25 EU Member States. A set of
data for assessing the economic impact of ageing”, European Commission Economic paper
N° 235, November 2005, available at:
http://europa.eu.int/comm/economy_finance/publications/economicpapers_en.htm
193
Cislaghi C., F.Tediosi, S.Bartolacci, R.Berni, S.Forni (2002), Hospital expenditure as
function of the distance from birth and death, Presentation at the 4th European Conference on
Health Economics, Université Paris V - 7-10 July 2002.
Comas-Herrera A., R.Wittenberg, L.Pickard (2005), Making projections of public expenditure
on long-term care for the European member states: Methodological proposal for discussion,
paper presented at the Commission-AWG-OECD workshop of 21/22 February 2005.
Cutler D. (1995), Technology, Health Costs and the NIH, Cambridge MA: Harvard
University and NBER, September.
Cutler D.M. and R.S.Huckman (2002), Technological Development and medical productivity:
Diffusion of Angioplasty in New York State, NBER Working paper, No.9311.
Cutler D. and M.McClellan (1996), The determinants of technological change in heart attack
treatment, NBER Working Paper, No. 5751.
Cutler D. and E.Meara (1997), The medical care costs of the young and the old: a forty year
perspective, NBER Working paper, No.6114.
Cutler D. and E.Meara (1999), The concentration of medical spending: An update, NBER
Working Paper, No.7279.
Cutler D.M., J.M.Poterba, L.M.Sheiner, L.H.Summers (1990), An Aging Society: opportunity
or Challenge?, Brookings Papers on Economic Activity, Vol.1, pp.1-73.
Cutler D.M., and L.Sheiner (1997), Managed Care and the Growth of Medical Expenditures,
NBER Working Paper, No.6140
Directorate General for Economic and Financial Affairs (2005), ‘The economic impact of
ageing populations: some insights from the ongoing work of DG ECFIN to the AWG’, Note
for the attention of the EPC, ECFIN(2005) REP 54200.
Docteur E. and H.Oxley (2003), Health care systems: lessons from the reform experience,
OECD
Directorate
for
Employment,
Labour
and
Social
Affairs,
DELSA/ELSA/WD/HEA(2003)9 of 5 December 2003.
Economic Policy Committee (2001), ‘The budgetary challenge posed by ageing populations’,
European Economy Reports and Studies N°4, European Commission, Directorate General for
Economic and Financial Affairs, available at:
http://europa.eu.int/comm/economy_finance/publications/european_economy/2001/eers0401_
en.pdf
Economic Policy Committee (2003), ‘The impact of ageing populations on public finances:
overview of analysis carried out at EU level and proposals for a work programme’.
http://europa.eu.int/comm/economy_finance/epc/documents/2003/pensionmaster_en.pdf
Economic Policy Committee and European Commission (2005a), “The 2005 EPC projections
of age-related expenditure (2004-2050) for the EU25 Member States: underlying assumptions
and projection methodologies” in European Economy Reports and Studies, No.4, availale at:
Brussels.http://europa.eu.int/comm/economy_finance/publications/european_economy/reports
andstudies0405_en.htm.
194
Economic Policy Committee and European Commission (2005b) “The 2005 EPC projections
of age-related expenditure: agreed underlying assumptions and projection methodologies” in
European Economy Occasional Papers N°19, availale at:
http://europa.eu.int/comm/economy_finance/publications/occasional_papers/occasionalpapers
19_en.htm.
Englert M., M.J.Festjens and M.Lopez-Novella (2004), L’évolution à long terme des dépenses
de soins de santé, Journée d’Etudes: ‘Budget 2005’, Institut Belge des Finances Publiques.
European Commission (2004) “The EU Economy 2004 review”, European Economy N°6,
availale at:
http://europa.eu.int/comm/economy_finance/publications/european_economy/the_eu_econom
y_review2004_en.htm
European Commission (2004a) Controlling health care expenditures: some recent
experiences with reform. Note for the attention of the Economic Policy Committee,
ECFIN/157/04-EN of 16 March 2004.
European Commission (2004b), Incorporating ‘death-related’ costs in long-term budgetary
projections of health care and long-term care: a review of existing methodologies and results.
Note for the attention of the Ageing Working Group attached to the EPC, ECFIN/C5/DC/BP
D(2004).
Eurostat (2004 a), ‘EUROPOP2004: methodology for drafting fertility assumptions in the
EU15 Member States’, ESTAT/F/1/POP/06(2004)/FS REV.1, 2 December 2004.
Eurostat (2005), ‘EU25 population rises until 2025, then falls’, Eurostat press release
448/2005 of 8 April 2005. For simplicity, the baseline variant of the trend scenario of
EUROPOP2004 is referred to as EUROPOP2004 baseline in the text.
Fogel R.W. (1994), Economic Growth, Population theory and Physiology: the Bearing of
Long-Term Processes on the making of Economic Policy, NBER Working Paper, No.4638.
Fogel R.W. (2002), Biotechnology and the Burden of Age-Related Diseases, in: OECD,
Healthy Ageing and Biotechnology. Policy Implications of New Research.
Fries J.F. (1980), Ageing, natural death, and the compression of morbidity, The New England
Journal of Medicine, Vol.303, pp.130-135.
Fries J.F. (1983), The compression of morbidity, Milbank Memorial Fund Quarterly, Vol.61,
pp.397-419.
Fries J.F. (1989), The compression of morbidity: near or far?, Milbank Memorial Fund
Quarterly, Vol.67, pp.208-232.
Fries J.F. (1993), Compression of morbidity: life span, disability, and health care costs, Facts
and Research in Gerontology, Vol.7, pp.183-190.
Fries J.F. (2003), Measuring and Monitoring Success in Compressing Morbidity, Annals of
Internal Medicine, Vol.139, pp.455-459.
195
Fuchs V.R. (1998a), Provide, provide: the economics of aging, NBER Working Paper,
No.6642.
Fuchs V.R. (1998b), Health care for the elderly: How much? Who will pay for it?, NBER
Working Paper, No.6755
Gabriele S., C.Cislaghi, F.Costantini, F.Innocenti, V.Lepore, F.Tediosi, M.Valerio,
C.Zocchetti (2005), Demographic factors and health expenditure profiles by age: the case of
Italy, deliverable for the ENEPRI AHEAD (Ageing, Health Status and Determinants of
Health Expenditure) project.
Garber A.M., T.E.MaCurdy, M.L.McClellan (1998), Medical care at the end of life: diseases,
treatment patterns, and costs, NBER Working Paper, No. 6748.
Gerdtham U.G. (1992), Pooling international health care expenditure data, Health
Economics, Vol.1, pp.217-231.
Gerdtham U.G., J.Sogaard, B.Jonsson, F.Andersson (1992a), A pooled cross-section analysis
of the health care expenditures of the OECD countries, Developments in Health Economics
And Public Policy, Vol.1, pp.287-310.
Gerdtham U.G., J.Sogaard, F.Andersson, B.Jonsson (1992b), An econometric analysis of
health care expenditure: a cross-section study of the OECD countries,
Journal of Health Economics, May, Vol.11(1), pp.63-84.
Gerdtham U.G., B.Jönsson, M.MacFarlan, H.Oxley (1994), Factors Affecting Health
Spending: a Cross-country Econometric Analysis, in: H.Oxley and M.MacFarland, Health
Care Reform. Controlling Spending and Increasing Efficiency, OECD Economics Department
Working Papers No.149, OCDE/GD(94)101.
Getzen, T.E. (1990), Macro Forecasting of National Health Expenditures, Advances in
Health Economics and Health Services Research, Vol.11, pp.27-48.
Getzen T.E. (2000), Health care is an individual necessity and a national luxury: Applying
multilevel decision models to the analysis of health care expenditures, Journal of Health
Economics, Vol.19(2), pp.259-270.
Grignon M. (2003), Les conséquences du vieillissement de la population sur les dépenses de
santé, in: Centre de Recherche, d’Etude et de Documentation en Economie de la Santé,
Questions d’économie de la santé, No.66.
Gruenberg E.M. (1977), The failure of success, Millbank Memorial Fund Quarterly, Vol.55,
pp.3-24.
Guralnik J.M. (1991), Prospects for the compression of morbidity: Evidence from the
Alameda County study, Journal of Aging and Health, Vol.3, pp.138-153.
Health Canada (2001), Health expenditures in Canada by Age and Sex : 1980-81 to 20002001
196
Henke K.D. and J.Schreyögg (2004), Towards sustainable health care systems. Strategies in
health insurance schemes in France, Germany, Japan and the Netherlands. A comparative
study, International Social Security Association.
Hitiris T. and J.Posnett (1992), The determinants and effects of health expenditure in
developed countries, Journal of Health Economics, Vol.11(2), pp.173-181.
Holly A. (2005), ‘Health-based predictive models: How to extrapolate existing medical
information into the projections of future health care expenditure?’, Presentation to the joint
EC-AWG-OECD workshop of 21-22 February 2005.
Howe Neil and Richard Jackson (2005) ‘Projecting immigration: a survey of the current state
of practice and theory’, Center for Strategic International Studies, a report of the CSIS Global
Aging Initiative.
Husson M. (2004), La santé, un bien supérieur ?, Chronique Internationale de l'IRES , No. 91
Jacobzone S. (2002), Healthy Ageing and the Challenges of New Technologies. Can OECD
Social and Health-Care Systems Provide for the Future?, in: OECD, Healthy Ageing and
Biotechnology. Policy Implications of New Research.
Kanavos P. and E.Mossialos (1996), The Methodology of International Comparisons of health
Care Expenditures: Any lessons for Health Policy?, Health and Social Care Discussion Paper
Series, No.3, London School of Economics and Political Science.
Kanavos P. and E.Mossialos (1999), International comparisons of health care expenditures:
what we know and what we do not know, Journal of Health Services Research & Policy, Vol.
4(2), pp.122-126.
Laditka S.B. and M.D.Hayward (2004), The Evolution of Demographic Methods to Calculate
Health Expectancies, in: J.-M.Robine, C.Jagger, C.D.Mathers, E.M.Crimmins, R.M.Suzman
(eds.), Determining Health Expectancies, John Wiley and Sons, Chichester, pp.221-234.
Leu R.E. (1986), The public-private mix and international health care costs, in A.J. Culyer
and B.Jönsson (eds.), Public and Private Health Services, Basil Blackwell, Oxford, pp.41-63
L’Horty Y., A.Quinet, F.Rupprecht (1997), Expliquer la croissance des dépenses de santé: le
rôle de niveau de vie et du progrès technique, Economie et Prévision, No.129-130, pp.255266.
Lubitz J., J.Beebe, C.Baker (1995), Longevity and Medicare Expenditures, The New England
Journal of Medicine, Vol.332, pp.999-1003.
Lubitz J.D. and G.F.Riley (1993), Trends in Medicare Payments in the Last Year of Life, The
New England Journal of Medicine, Vol.328, pp.1092-1096.
Madsen M. (2004), Methodologies to incorporate ‘death-related’ costs in projections of
health and long-term care based on Danish data, Ministry of Finance, Denmark.
Mahal A. and P.Berman (2001), Health Expenditures and the Elderly: A Survey of Issues in
Forecasting, Methods Used, and Relevance for Developing Countries, Harvard Burden of
197
Disease Unit, The Global Burden of Disease 2000 in Aging Populations, Research Paper No.
01.23.
Manton K.G. (1982), Changing concepts of morbidity and mortality in the elderly population,
Milbank Memorial Fund Quarterly, Vol.60, pp.183-244.
Manton K.G., E.Stallard, L.Corder (1995); Changes in morbidity and chronic disability in the
U.S. elderly population: Evidence from the 1982, 1984 and 1989 National Long Term Care
Surveys, Journal of Gerontology: Social Sciences, No.50(4), pp.S194-S204.
Maslow A.H. (1970), Motivation and Personality, Longman, New York.
McDonald P. (2000), The ‘Toolbox’ of Public Policies to Impact on Fertility – a Global View,
Paper presented at the seminar ‘Low fertility, families and public policies’ organised by the
European Observatory on Family Matters in Sevilla, September 15-16, 2000.
McDonald P. (2002), Low fertility: unifying the theory and the demography, Paper prepared
for Session 73, Future of fertility in Low Fertility Countries, 2002 Meeting of the Population
Association of America, Atlanta, 9-11 May 2002.
Meerding W.J., L.Bonneux, J.J.Polder, M.A.Koopmanschap, P.J.van der Maas (1998),
Demographic and epidemiological determinates of health care costs in the Netherlands.
British Medical Journal, No.317, pp.111-115.
Miller T. (2001), Increasing Longevity and Medicare Expenditures, Demography, Vol.38(2),
pp.215-226.
Ministry of Health, Welfare and Sport, The Netherlands (2004), Health Care in an Ageing
Society. A Challenge for all European Countries, Background Paper of the Netherlands EU
Presidency, Informal Health Council, Noordwijk, 9 – 10 September 2004.
Murillo C., C.Piatecki, M.Saez (1993), Health care expenditure and income in Europe,
Health Economics. Vol.2(2), pp.127-28.
Murthy N.R.V. and V. Ukpolo (1994), Aggregate health care expenditure in the United
States, Applied Economics, Vol.26, pp.797-802.
Newhouse J.P. (1977), Medical care expenditure: a cross national survey, Journal of Human
Resources, Vol.12, pp.115-125.
Newhouse J.P. (1992), Medical Care Costs: How Much Welfare Loss?, Journal of Economic
Perspectives, Summer, Vol.6(3), pp.3-21.
Nichols L.M. (2002), Can Defined Contribution Health Insurance Reduce Cost Growth?,
EBRI Issue Brief No.246.
Nusselder W. (2003), Compression of Morbidity, in: J.-M.Robine, C.Jagger, C.D.Mathers,
E.M.Crimmins, R.M.Suzman (eds.), Determining Health Expectancies, John Wiley and Sons,
Chichester, pp.35-58.
Nusselder W., J.Mackenbach (1997), Rectangularisation of the survival curve in the
Netherlands, Journal of Gerontology: Social Sciences 52b, pp.S145-S154.
198
OECD (1998), Health Policy Brief. Ageing and Technology, Working Party on
Biotechnology, DSTI/STP/BIO(97)13 of 17 June 1998.
OECD (2003), ‘Towards high performing health systems – Draft report to Ministers on the
OECD Health Project”, Ad hoc Group on the OECD Health Project,
SG/ADHOC/HEA(2003)20 of 18 November 2003.
OECD Health Data 2004.
OECD Health Data 2005
Oeppen J. and J.W.Vaupel (2002), Broken Limits to Life Expectancy, Science, Vol.296,
pp.1029-1031.
Okunade A.A and V.N.R.Murthy (2002), Technology as a ‘major driver’ of health care costs:
a cointegration analysis of the Newhouse conjecture, Journal of Health Economics,
Vol.21(1), pp.147-159.
Olshansky S.J., M.A.Rudberg, B.A.Carnes, C.K.Cassel, J.A.Brody (1991), Trading off longer
life for worsening health, Journal of Aging and health, Vol.3, pp.194-216.
Pellikaan F. and E.Westerhout (2004), Alternative scenarios for health, life expectancy and
social expenditure. The influence of living longer in better health on health expenditures,
pension expenditures and government finances in the EU, in: The AGIR Project. Ageing,
Health and Retirement in Europe, The Hague.
Productivity Commission (2004), Economic Implications of an Ageing Australia, Draft
Research Report, Productivity Commission, Canberra.
Ragioneria Generale dello Stato (2004), How to take account of death related costs in
projecting health care expenditure – the evidence for Italy and a proposal for the EPC-WGA.
Reinhardt U.E. (2000), Health Care for the Ageing Baby Boom: Lessons from Abroad, The
Journal of Economic perspectives, Vol.14(2), pp.71-83.
Riedel M., M.M.Hofmarcher, R.Buchegger, J.Brunner (2002),
Gesundheitswesen, Teil II, Institut für Höhere Studien (IHS), Wien.
Nachfragemodell
Robine J.M. and C.D.Mathers (1993), Measuring the compression or expansion of morbidity
through changes in health expectancy, in: J.M.Robine, C.D.Mathers, M.Bone, I.Romieu
(eds.), Calculation of Health Expectancies: Harmonization, Consensus Achieved and Future
Perspectives, John Libbey Eurotext, Montrouge, pp.269-286.
Robine J.M. and J.W.Vaupel (2002), Emergence of supercentenarians in low mortality
countries, available at: http://user.demogr.mpg.de/jwv/pdf/AmActJournal2002.pdf.
Robine J.M. and J.P.Michel (2004), Looking Forward to a General Theory on Population
Aging, Journal of Gerontology: Medical Sciences, Vol.59A, No.6, pp.590-597.
Robine J.M., C.Jagger, H.van Oyen (2005), Interpreting national evidence on the evolution of
morbidity and disability prevalence over time and perspectives for extended healthy life
expectancy, presentation at the Joint EU-OECD workshop, February 21-22, 2005.
199
Rochaix L. and S.Jacobzone (1997), L’hypothèse de demande induite : un bilan économique,
Economie et Prévision, No.129-130, pp. 25-35.
Suzman R., F.Kinsella, G.Myers (1992), Demography of older populations in developed
countries, in J.G.Evans, T.F. Williams (eds.), Oxford Textbook of Geriatric Medicine, Oxford
Medical Publications, pp.3-14, Oxford
Verbrugge L.M. (1984), Longer life but worsening health? Trends in health and mortality of
middle-aged and older persons, Milbank Memorial Fund Quarterly, Vol. 62, pp.475-519.
Wanless D. (2002), Securing our Future Health: Taking a Long-Term View. Final report, HM
Treasury.
Weisbrod B. (1991), The Health Care Quadrilemma: An Essay on Technological Change,
Insurance, Quality of Care and Cost Containment, Journal of Economic Literature, June
Vol.24, pp.523-552.
World Health Organisation (2003), International Statistical Classification of Diseases and
Related Health Problems.10th Revision. Version for 2003; available at:
http://www3.who.int/icd/vol1htm2003/fr-icd.htm.
World Health Organization Regional Office for Europe, European health for all database
(HFA-DB), available at: http://data.euro.who.int/hfadb/
Zweifel P., S.Felder, M.Meiers (1999), Ageing of population and health care expenditure: a
red herring?, Health Economics, Vol.8(6), pp.485-496.
200
LIST OF TABLES
Table 1-1 Overview of underlying assumptions and adjustments for certain Member States. 23
Table 2-1 Baseline assumptions on fertility rates in EU Member states ................................. 26
Table 2-2 Baseline assumptions on life expectancy at birth for males and females ................ 28
Table 2-3 Baseline assumptions on net migration flows for EU Member States .................... 31
Table 2-4 Overview of the projected changes in the size and age structure of the .....................
population, in millions...................................................................................................... 33
Table 2-5 Participation rates by gender and age group in 2003 in EU Member States ........... 37
Table 2-6 Projected changes in participation rates up to 2050 used in the baseline scenario.. 37
Table 2-7 Assumptions on unemployment rates ...................................................................... 39
Table 2-8 Projected employments rates used in the 2005 EPC budgetary projection exercise42
Table 2-9 Projected changes in employment (aged 15-64)...................................................... 43
Table 2-10 Peaks and troughs for the size of the working-age population and the total number
of persons employed (aged 15-64) ................................................................................... 45
Table 2-11 Projected potential growth rates and determinants ................................................ 47
Table 2-12 GDP growth and its sources, 2004-2050 ............................................................... 49
Table 2-13 GDP per capita growth: growth rates and levels relative to EU15 average .......... 50
Table 2-14 Projected changes in demographic and economic dependency ratios ................... 52
Table 3-1 Overview of the pension systems in Member States ............................................... 56
Table 3-2 Coverage of pension schemes in the 2004 projections ............................................ 63
Table 3-3 Gross public pension expenditure as a share of GDP between 2004 and 2050....... 71
Table 3-4 Comparison of the 2005 projections of gross public pension expenditure as a share
of GDP with the 2001 projections.................................................................................... 73
Table 3-5 Life expectancies in the 2004 and 2001 population projections............................. 76
Table 3-6 Dependency ratios in the 2004 and 2001 population projections............................ 76
Table 3-7 Peaks in public pension expenditure as a share of GDP.......................................... 77
Table 3-8 Old-age and early pensions, gross, as a share of all public pensions ...................... 80
Table 3-9 Disability and survivors’ pensions as a share of GDP between 2004 and 2050...... 81
201
Table 3-10 The contribution of the decomposed factors to the change (in percentage points) in
all public pensions relative to GDP.................................................................................. 83
Table 3-11 The projected benefit ratio: Average public pension relative to output per worker
.......................................................................................................................................... 85
Table 3-12 The contribution of the decomposed factors to the change (in percentage points) in
the public old-age and early pensions relative to GDP .................................................... 86
Table 3-13 Decomposition of the increase (in %) in public pension expenditure between 2005
and 2050 ........................................................................................................................... 87
Table 3-14 Decomposition of the increase (in %) in public old-age and early pension
expenditure between 2005 and 2050................................................................................ 88
Table 3-15 Annual growth rates of public old-age and early pensions over selected time
periods and decomposed by driving factors..................................................................... 89
Table 3-16 Occupational and private statutory pensions as a share of GDP between 2004 and
2050.................................................................................................................................. 92
Table 3-17 Total pension expenditure as a share of GDP between 2004 and 2050................. 93
Table 3-18 Benefit ratio: average total pension relative to output per worker ....................... 94
Table 3-19 Number of pensioners in public pension schemes................................................. 96
Table 3-20 Number of pensioners receiving public pensions relative to the population aged 65
and over ............................................................................................................................ 97
Table 3-21 Pension system dependency ratio: number of pensioners relative to the number of
contributors in public pension schemes ........................................................................... 98
Table 3-22 Number of contributors to public pension schemes............................................... 99
Table 3-23 Support ratio: Number of contributors relative to the number of pensioners in
public pension schemes.................................................................................................. 100
Table 3-24 Pension contributions to public pension schemes as a share of GDP.................. 101
Table 3-25 Social security pension contributions relative to public pensions ....................... 102
Table 3-26 Assets in public pension schemes as a share of GDP .......................................... 103
Table 3-27 Assets in all pension schemes as a share of GDP ................................................ 104
Table 3-28 Summary of the changes in gross public pension expenditure increases as a share
of GDP between 2004 and 2050 ................................................................................... 107
Table 3-29 Summary of the changes in all pension expenditure increases as a share of GDP
between 2004 and 2050.................................................................................................. 108
Table 3-30 Summary of changes in total assets as a % of GDP between 2004 and 2050 ..... 108
202
Table 3-31 Summary of changes in the ratio between contributions and pension expenditure
in public schemes between 2004 and 2050 .................................................................... 109
Table 4-1 The drivers of health care spending: how they are incorporated in the projection
exercise........................................................................................................................... 116
Table 4-2 Overview of different approaches used to make the projections on health care
spending ......................................................................................................................... 120
Table 4-3 A comparison of the age-related expenditure profiles – males ............................. 123
Table 4-4 A comparison of the age-related expenditure profiles – females .......................... 123
Table 4-5 Ratio between cost borne by a decedent and a survivor, by age cohort - males.... 126
Table 4-6 Ratio between cost borne by a decedent and a survivor, by age cohort - females 126
Table 4-7 Elasticity of health care spending per capita with respect to GDP per capita ....... 127
Table 4-8 Projection results for the pure ageing scenario (I): public spending on health care as
% of GDP ....................................................................................................................... 128
Table 4-9 Projection results for constant health scenario (II) ............................................... 129
Table 4-10 Projection results for the death-related costs scenario (III) ................................. 130
Table 4-11 Projection results for scenario IV capturing a positive income elasticity of demand
for health care spending ................................................................................................. 131
Table 4-12 Projection results for scenario V where unit costs evolve in line with GDP per
worker............................................................................................................................. 132
Table 4-13 Projection results for AWG reference scenario ................................................... 133
Table 4-14 Overview of projected changes in health care spending as a % of GDP between
2004 and 2050 ................................................................................................................ 135
Table 4-15 Difference in the projected changes in health care spending 2004-2050 between
Scenario I (pure ageing, costs evolve in line with GDP per capita, using national agerelated expenditure profiles) and the other scenarios..................................................... 135
Table 5-1 Overview of scenarios ........................................................................................... 143
Table 5-2 Overview of data availability................................................................................. 145
Table 5-3 Age-related expenditure profiles for long-term care, in euros and GDP per ..............
capita – males ................................................................................................................. 147
Table 5-4 Age-related expenditure profiles for long-term care in euros and GDP per
capita
– females ........................................................................................................................ 147
Table 5-5 Dependency rates among elderly population in households, by age .........
group
........................................................................................................................................ 149
203
Table 5-6 Estimated elderly dependent population in 2004 for 8 EU Member States, in
thousands (based on SHARE data and reported number of people in institutions) ....... 150
Table 5-7 Estimated size of dependent population in 2004 using ‘average’ dependency rates
by age and gender from SHARE data, in thousands ...................................................... 151
Table 5-8 Total dependent population estimated, EU25, in thousands.................................. 151
Table 5-9 Estimated ADL-dependent population aged 65 and above, 2004 ......................... 152
Table 5-10 Total public expenditure on long-term care, all ages, 2004, as a % of GDP....... 153
Table 5-11 Projection of dependent population, pure ageing scenario .................................. 155
Table 5-12Projection of dependent population, in thousands – constant disability scenario
........................................................................................................................................ 156
Table 5-13 Projection results for the pure ageing scenario (I) ............................................... 157
Table 5-14 Projection results for the scenario where unit costs evolve in line with GDP per
capita (II) ........................................................................................................................ 158
Table 5-15 Projection results for the constant disability scenario (III).................................. 159
Table 5-16 Projection of dependent population, in thousands – increase in formal care
provision......................................................................................................................... 160
Table 5-17 Projection results for the increase in formal care provision scenario (IV) .......... 161
Table 5-18 Projection results for the AWG reference scenario ............................................. 162
Table 6-1: Detailed assumptions made in performing the projections................................... 165
Table 6-2: Change in population aged 5-25 and young share of working-age population
between 2002 and 2050.................................................................................................. 169
Table 6-3: Labour market participation rates for young people (2002-2050)........................ 170
Table 6-4: Enrolment rate across all level of education by age1. 2002 ................................. 171
Table 6-5: Enrolment rate across all level of education by age1. 2003 ................................. 172
Table 6-6: Enrolment rate across all level of education by age1. 2050 ................................. 173
Table 6-7: Total number of students and student share of working-age population.............. 174
Table 6-8: Percentage share of education publicly funded (2002)......................................... 175
Table 6-9: Total public expenditure on education as a share of GDP (2002-2050)............... 176
Table 6-10: Education expenditure as a share of GDP compared to the young-age population
(defined as aged 5-25), the total number of students and the share of students over
population aged 15-64. Percentage changes 2002-2050 ................................................ 178
204
Table 6-11: Decomposition of the change in the education expenditure to GDP-ratio.
Percentage point contribution from different factors. 2002-2050.................................. 180
Table 6-12: Expenditure on education as share of GDP. EU15. 1990-2003 ......................... 182
Table 7-1 - Social protection expenditure as % of GDP: Unemployment ............................. 186
Table 7-2 – Unemployment benefit spending, as % of GDP ................................................. 187
Table 7-3 Unemployment benefit spending per unemployed, as % of GDP per worker (yubpc) ...... 188
Table 7-4 –Unemployment rate – (AWG baseline scenario)................................................. 189
Table 7-5 –Unemployment/Employment ratio (U/L) ............................................................ 189
Table 7-6- Projections of unemployment benefit spending, as % of GDP ............................ 190
205
LIST OF GRAPHS
Graph 1-1
Overview of the 2005 projection of age-related expenditure........................... 22
Graph 2-1 Past and projected fertility rates for the EU25........................................................ 26
Graph 2-2 Baseline assumptions for life expectancy at birth, EU 15 and EURO.................... 27
Graph 2-3 Baseline assumptions on net migration flows, EU 15 and EURO......................... 30
Graph 2-4 Age pyramids for the EU25 population in 2004 and 2050 ..................................... 34
Graph 2-5 Projected changes in the age structure of the EU25 population ............................. 34
Graph 2-6 Baseline labour force projection (change in % of people aged 15-64 between 2003
and 2050).......................................................................................................................... 38
Graph 2-7 Projected employment rates and Lisbon targets in the EU25 ................................. 41
Graph 2-8 Projected changes in employment (% change of employed people aged 15-64
between 2003 and 2050) .................................................................................................. 44
Graph 2-9 Projected working-age population and total employment, EU25........................... 45
Graph 2-10 Projected potential GDP growth (annual average) in the EU25 Member States .. 48
Graph 2-11 Projected (annual average) potential growth rates in the EU15 and EU10 and their
determinants (employment/productivity)......................................................................... 48
Graph 2-12 Projected demographic and economic dependency ratios for the EU 25 ............. 51
Graph 3-1 Gross and net public pension expenditure as a share of GDP in 2004 ................... 78
Graph 3-2 Public, occupational and private mandatory pensions as a share of GDP in 2004,
2030 and 2050 .................................................................................................................. 95
Graph 4-1 Illustration of the different scenarios for future morbidity/disability and longevity
using age profiles on health care costs ........................................................................... 119
Graph 4-2 Age related expenditure profiles for EU Member States, males and females ...... 122
Graph 4-3 Average age-related expenditure profiles for the EU15 and EU10 (males and
females) .......................................................................................................................... 124
Graph 5-1
Model structure .............................................................................................. 141
Graph 5-2 Age-related expenditure profiles for long-term care, % of GDP per capita, males,
2004................................................................................................................................ 148
Graph 5-3 Age-related expenditure profiles for long-term care in Euros, males, 2004......... 148
206
Graph 5-4 Age-related expenditure profiles for long-term care, % of GDP per capita, females,
2004................................................................................................................................ 148
Graph 5-5 Age-related expenditure profiles for long-term care in Euros, females, 2004...... 148
Graph 5-6 Age-related expenditure profiles for long-term care, % of GDP per capita, males,
2004................................................................................................................................ 148
Graph 5-7 Age-related expenditure profiles for long-term care in Euros, males, 2004......... 148
Graph 5-8 Age-related expenditure profiles for long-term care, % of GDP per capita, females,
2004................................................................................................................................ 148
Graph 5-9 Age-related expenditure profiles for long-term care in Euros, females, 2004...... 148
Graph 6-1: Population aged 5-25 and over 65 in the EU25 (2002-2050). ............................ 168
Graph 6-2: Rate of change of population aged 5-25 between 1990 and 2003. ...................... 181
207